Name: Azure Data Factory for Beginners - Build Data Ingestion
Price: 22.99 GBP
Availability: InStock

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					<div><p> </p><p>The comprehensive Diploma in Data Engineering with Google BigQuery &amp; Google Cloud has been designed by industry experts to provide learners with everything they need to enhance their skills and knowledge in their chosen area of study. Enrol on the Diploma in Data Engineering with Google BigQuery &amp; Google Cloud today, and learn from the very best the industry has to offer!</p></div>
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					<div><p>This best selling Diploma in Data Engineering with Google BigQuery &amp; Google Cloud has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Diploma in Data Engineering with Google BigQuery &amp; Google Cloud is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</p><p>The Diploma in Data Engineering with Google BigQuery &amp; Google Cloud is CPD-accredited, so you can be confident you're completing a quality training course  will boost your CV and enhance your career potential. The Diploma in Data Engineering with Google BigQuery &amp; Google Cloud is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn.</p><p>After successfully completing the Diploma in Data Engineering with Google BigQuery &amp; Google Cloud, you will be awarded a certificate of completion  as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the Diploma in Data Engineering with Google BigQuery &amp; Google Cloud will help you stand out from the crowd. You can also validate your certification on our website.</p><p>We know that you are busy and that time is precious, so we have designed the Diploma in Data Engineering with Google BigQuery &amp; Google Cloud to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device. </p><p>Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.</p></div>
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Course Cloud

Diploma in Data Engineering with Google BigQuery & Google Cloud

General Admission

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				<p><span>Register on the Data Engineering with Google BigQuery &amp; Google Cloud today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career.</span></p><p><span>The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials.</span></p><p><span>Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get an e-certificate as proof of your course completion.</span></p><p><span>The Data Engineering with Google BigQuery &amp; Google Cloud is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones.</span></p><p><span>The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly!</span></p><h5><b>What You Get With The Data Engineering with Google BigQuery &amp; Google Cloud</b></h5><ul><li><span>Receive a e-certificate upon successful completion of the course</span></li><li><span>Get taught by experienced, professional instructors</span></li><li><span>Study at a time and pace that suits your learning style</span></li><li><span>Get instant feedback on assessments </span></li><li><span>24/7 help and advice via email or live chat</span></li><li><span>Get full tutor support on weekdays (Monday to Friday)</span></li></ul>					</div>
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			<h2>Course Design</h2>		</div>
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				<div id="course-home"><div><p><span>The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace.</span></p><p><span>You are taught through a combination of</span></p><ul><li><span>Video lessons</span></li><li><span>Online study materials</span></li></ul></div></div>					</div>
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			<h2>Certification</h2>		</div>
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				<p><span>Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99.</span></p>					</div>
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			<h2>Who Is This Course For:</h2>		</div>
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				<p><span>The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge.</span></p>					</div>
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			<h2>Requirements:</h2>		</div>
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				<p><span>The online training is open to all students and has no formal entry requirements. To study the Data Engineering with Google BigQuery &amp; Google Cloud, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16.</span></p>					</div>
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				<h3>Course Content</h3>

<div id="course_curriculum">
<table width="100%">				<tbody><tr>
					<td colspan="4">Unit 01: Introduction</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 01: Welcome to This Course</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
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					<td>Module 02: How to Get Maximum Value from This Course</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
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					<td>Module 03: Course Structure &amp; Coverage</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
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					<td>Module 04: Technology in This Course</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
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					<td colspan="4">Unit 02: Introducing Data Warehouse &amp; BigQuery</td>
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					<td>Module 01: Data Warehouse</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
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					<td>Module 02: Start With BigQuery</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
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					<td>Module 03: BigQuery Web User Interface</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
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					<td colspan="4">Unit 03: First Exploration</td>
				</tr>
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					<td>Module 01: First Data</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
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					<td>Module 02: Basic Exploration</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
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					<td>Module 03: Functions</td>
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
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					<td>Module 04: Common Data Types</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
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					<td>Module 05: Different Query</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
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					<td>Module 06: Exploring Common Data Types</td>
					<td> </td>
					<td><span><i></i> 00:25:00</span></td>
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					<td>Module 07: Converting Data Types</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
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					<td colspan="4">Unit 04: Data Flow Basic</td>
				</tr>
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					<td>Module 01: Data Quality</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
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					<td>Module 02: Clean &amp; Transform</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
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					<td>Module 03: Store Data</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
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					<td>Module 04: Upgrading From Sandbox Account</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
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					<td>Module 05: Clean &amp; Transform With Dataprep</td>
					<td> </td>
					<td><span><i></i> 00:25:00</span></td>
				</tr>
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					<td>Module 06: Scheduled Query</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
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					<td>Module 07: Analyze Data</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
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					<td>Module 08: Data Visualization</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
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					<td colspan="4">Unit 08: Intermediate Query</td>
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					<td>Module 01: Essential BigQuery</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
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					<td>Module 02: Load Data into BigQuery (Part 1) - The Basic</td>
					<td> </td>
					<td><span><i></i> 00:36:00</span></td>
				</tr>
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					<td>Module 03: Tip: Mock Data</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
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					<td>Module 04: Load Data into BigQuery (Part 2) - Handling Errors</td>
					<td> </td>
					<td><span><i></i> 00:22:00</span></td>
				</tr>
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					<td>Module 05: Load Data into BigQuery (Part 3) - Efficient Load</td>
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Module 06: Load Data into BigQuery (Part 4) - From Your Data to BigQuery</td>
					<td> </td>
					<td><span><i></i> 00:23:00</span></td>
				</tr>
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					<td>Module 07: Load Data into BigQuery (Part 5) - In Microservice Architecture</td>
					<td> </td>
					<td><span><i></i> 00:20:00</span></td>
				</tr>
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					<td>Module 08: Tip: Message Broker Overview</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
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					<td>Module 09: Load Data into BigQuery (Part 6) - Recurring Load</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 05: Diving into BigQuery</td>
				</tr>
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					<td>Module 01: BigQuery View</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Unit 06: Virtual Data using View</td>
				</tr>
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					<td><i></i></td>
					<td>Module 01: What We Will Learn</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Google Sheets &amp; BigQuery</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
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					<td><i></i></td>
					<td>Module 03: Google Data Studio</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
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					<td colspan="4">Unit 07: Data Visualization</td>
				</tr>
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					<td><i></i></td>
					<td>Module 01: Using Join - Theory</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 02: Using Join - Hands On</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 03: Union &amp; Intersect</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Module 04: Basic Statistical Functions</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
				</tbody></table></div>

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			<h2>Frequently Asked Questions</h2>
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                                    Are there any prerequisites for taking the course?
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                                    <p>
                                        There are no specific prerequisites for this course, nor
                                        are there any formal entry requirements. All you need is
                                        an internet connection, a good understanding of English
                                        and a passion for learning for this course.
                                    </p>
                                </div>
                            </div>
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                                    Can I access the course at any time, or is there a set
                                    schedule?
                                </span>
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                                    <p>
                                        You have the flexibility to access the course at any time
                                        that suits your schedule. Our courses are self-paced,
                                        allowing you to study at your own pace and convenience.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
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                                <span>
                                    How long will I have access to the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        For this course, you will have access to the course
                                        materials for 1 year only. This means you can review the
                                        content as often as you like within the year, even after
                                        you've completed the course. However, if you buy Lifetime
                                        Access for the course, you will be able to access the
                                        course for a lifetime.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    Is there a certificate of completion provided after
                                    completing the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
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                                    <p>
                                        Yes, upon successfully completing the course, you will
                                        receive a certificate of completion. This certificate can
                                        be a valuable addition to your professional portfolio and
                                        can be shared on your various social networks.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    Can I switch courses or get a refund if I'm not satisfied
                                    with the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        We want you to have a positive learning experience. If
                                        you're not satisfied with the course, you can request a
                                        course transfer or refund within 14 days of the initial
                                        purchase.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    How do I track my progress in the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        Our platform provides tracking tools and progress
                                        indicators for each course. You can monitor your progress,
                                        completed lessons, and assessments through your learner
                                        dashboard for the course.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    What if I have technical issues or difficulties with the
                                    course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        If you encounter technical issues or content-related
                                        difficulties with the course, our support team is
                                        available to assist you. You can reach out to them for
                                        prompt resolution.
                                    </p>
                                </div>
                            </div>
                        </div>

Janets

Online Course Marketing

Online Course Creation

Data Engineering

Google Cloud

Trainers Course

Google Digital Marketing

Data Engineering with Google BigQuery & Google Cloud

<div id="course-pills-1">Duration<p>4 Days</p><p>24 CPD hours</p>This course is intended for<p>This class is intended for experienced developers who are responsible for managing big data transformations including:<br />Extracting, loading, transforming, cleaning, and validating data.<br />Designing pipelines and architectures for data processing.<br />Creating and maintaining machine learning and statistical models.<br />Querying datasets, visualizing query results and creating reports</p>Overview<p>Design and build data processing systems on Google Cloud Platform.<br />Leverage unstructured data using Spark and ML APIs on Cloud Dataproc.<br />Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow.<br />Derive business insights from extremely large datasets using Google BigQuery.<br />Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML.<br />Enable instant insights from streaming data</p><p>Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data.</p></div><div id="course-pills-2"><h4>Introduction to Data Engineering</h4><ul><li>Explore the role of a data engineer.</li><li>Analyze data engineering challenges.</li><li>Intro to BigQuery.</li><li>Data Lakes and Data Warehouses.</li><li>Demo: Federated Queries with BigQuery.</li><li>Transactional Databases vs Data Warehouses.</li><li>Website Demo: Finding PII in your dataset with DLP API.</li><li>Partner effectively with other data teams.</li><li>Manage data access and governance.</li><li>Build production-ready pipelines.</li><li>Review GCP customer case study.</li><li>Lab: Analyzing Data with BigQuery.</li></ul><h4>Building a Data Lake</h4><ul><li>Introduction to Data Lakes.</li><li>Data Storage and ETL options on GCP.</li><li>Building a Data Lake using Cloud Storage.</li><li>Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions.</li><li>Securing Cloud Storage.</li><li>Storing All Sorts of Data Types.</li><li>Video Demo: Running federated queries on Parquet and ORC files in BigQuery.</li><li>Cloud SQL as a relational Data Lake.</li><li>Lab: Loading Taxi Data into Cloud SQL.</li></ul><h4>Building a Data Warehouse</h4><ul><li>The modern data warehouse.</li><li>Intro to BigQuery.</li><li>Demo: Query TB+ of data in seconds.</li><li>Getting Started.</li><li>Loading Data.</li><li>Video Demo: Querying Cloud SQL from BigQuery.</li><li>Lab: Loading Data into BigQuery.</li><li>Exploring Schemas.</li><li>Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA.</li><li>Schema Design.</li><li>Nested and Repeated Fields.</li><li>Demo: Nested and repeated fields in BigQuery.</li><li>Lab: Working with JSON and Array data in BigQuery.</li><li>Optimizing with Partitioning and Clustering.</li><li>Demo: Partitioned and Clustered Tables in BigQuery.</li><li>Preview: Transforming Batch and Streaming Data.</li></ul><h4>Introduction to Building Batch Data Pipelines</h4><ul><li>EL, ELT, ETL.</li><li>Quality considerations.</li><li>How to carry out operations in BigQuery.</li><li>Demo: ELT to improve data quality in BigQuery.</li><li>Shortcomings.</li><li>ETL to solve data quality issues.</li></ul><h4>Executing Spark on Cloud Dataproc</h4><ul><li>The Hadoop ecosystem.</li><li>Running Hadoop on Cloud Dataproc.</li><li>GCS instead of HDFS.</li><li>Optimizing Dataproc.</li><li>Lab: Running Apache Spark jobs on Cloud Dataproc.</li></ul><h4>Serverless Data Processing with Cloud Dataflow</h4><ul><li>Cloud Dataflow.</li><li>Why customers value Dataflow.</li><li>Dataflow Pipelines.</li><li>Lab: A Simple Dataflow Pipeline (Python/Java).</li><li>Lab: MapReduce in Dataflow (Python/Java).</li><li>Lab: Side Inputs (Python/Java).</li><li>Dataflow Templates.</li><li>Dataflow SQL.</li></ul><h4>Manage Data Pipelines with Cloud Data Fusion and Cloud Composer</h4><ul><li>Building Batch Data Pipelines visually with Cloud Data Fusion.</li><li>Components.</li><li>UI Overview.</li><li>Building a Pipeline.</li><li>Exploring Data using Wrangler.</li><li>Lab: Building and executing a pipeline graph in Cloud Data Fusion.</li><li>Orchestrating work between GCP services with Cloud Composer.</li><li>Apache Airflow Environment.</li><li>DAGs and Operators.</li><li>Workflow Scheduling.</li><li>Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery.</li><li>Monitoring and Logging.</li><li>Lab: An Introduction to Cloud Composer.</li></ul><h4>Introduction to Processing Streaming Data</h4><ul><li>Processing Streaming Data.</li></ul><h4>Serverless Messaging with Cloud Pub/Sub</h4><ul><li>Cloud Pub/Sub.</li><li>Lab: Publish Streaming Data into Pub/Sub.</li></ul><h4>Cloud Dataflow Streaming Features</h4><ul><li>Cloud Dataflow Streaming Features.</li><li>Lab: Streaming Data Pipelines.</li></ul><h4>High-Throughput BigQuery and Bigtable Streaming Features</h4><ul><li>BigQuery Streaming Features.</li><li>Lab: Streaming Analytics and Dashboards.</li><li>Cloud Bigtable.</li><li>Lab: Streaming Data Pipelines into Bigtable.</li></ul><h4>Advanced BigQuery Functionality and Performance</h4><ul><li>Analytic Window Functions.</li><li>Using With Clauses.</li><li>GIS Functions.</li><li>Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz.</li><li>Performance Considerations.</li><li>Lab: Optimizing your BigQuery Queries for Performance.</li><li>Optional Lab: Creating Date-Partitioned Tables in BigQuery.</li></ul><h4>Introduction to Analytics and AI</h4><ul><li>What is AI?.</li><li>From Ad-hoc Data Analysis to Data Driven Decisions.</li><li>Options for ML models on GCP.</li></ul><h4>Prebuilt ML model APIs for Unstructured Data</h4><ul><li>Unstructured Data is Hard.</li><li>ML APIs for Enriching Data.</li><li>Lab: Using the Natural Language API to Classify Unstructured Text.</li></ul><h4>Big Data Analytics with Cloud AI Platform Notebooks</h4><ul><li>What's a Notebook.</li><li>BigQuery Magic and Ties to Pandas.</li><li>Lab: BigQuery in Jupyter Labs on AI Platform.</li></ul><h4>Production ML Pipelines with Kubeflow</h4><ul><li>Ways to do ML on GCP.</li><li>Kubeflow.</li><li>AI Hub.</li><li>Lab: Running AI models on Kubeflow.</li></ul><h4>Custom Model building with SQL in BigQuery ML</h4><ul><li>BigQuery ML for Quick Model Building.</li><li>Demo: Train a model with BigQuery ML to predict NYC taxi fares.</li><li>Supported Models.</li><li>Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML.</li><li>Lab Option 2: Movie Recommendations in BigQuery ML.</li></ul><h4>Custom Model building with Cloud AutoML</h4><ul><li>Why Auto ML?</li><li>Auto ML Vision.</li><li>Auto ML NLP.</li><li>Auto ML Tables.</li></ul></div>

Nexus Human

Google Data Analytics

Big Data Analytics

Data Science

Data Skills

Data Engineering on Google Cloud

<div id="course-pills-1">Duration<p>1 Days</p><p>6 CPD hours</p>This course is intended for<p>The primary audience for this course is data professionals who are familiar with data modeling, extraction, and analytics. It is designed for professionals who are interested in gaining knowledge about Lakehouse architecture, the Microsoft Fabric platform, and how to enable end-to-end analytics using these technologies.<br />Job role: Data Analyst, Data Engineer, Data Scientist</p>Overview<p>Describe end-to-end analytics in Microsoft Fabric<br />Describe core features and capabilities of lakehouses in Microsoft Fabric<br />Create a lakehouse<br />Ingest data into files and tables in a lakehouse<br />Query lakehouse tables with SQL<br />Configure Spark in a Microsoft Fabric workspace<br />Identify suitable scenarios for Spark notebooks and Spark jobs<br />Use Spark dataframes to analyze and transform data<br />Use Spark SQL to query data in tables and views<br />Visualize data in a Spark notebook<br />Understand Delta Lake and delta tables in Microsoft Fabric<br />Create and manage delta tables using Spark<br />Use Spark to query and transform data in delta tables<br />Use delta tables with Spark structured streaming<br />Describe Dataflow (Gen2) capabilities in Microsoft Fabric<br />Create Dataflow (Gen2) solutions to ingest and transform data<br />Include a Dataflow (Gen2) in a pipeline</p><p>This course is designed to build your foundational skills in data engineering on Microsoft Fabric, focusing on the Lakehouse concept. This course will explore the powerful capabilities of Apache Spark for distributed data processing and the essential techniques for efficient data management, versioning, and reliability by working with Delta Lake tables. This course will also explore data ingestion and orchestration using Dataflows Gen2 and Data Factory pipelines. This course includes a combination of lectures and hands-on exercises that will prepare you to work with lakehouses in Microsoft Fabric.</p></div><div id="course-pills-2"><h4>Introduction to end-to-end analytics using Microsoft Fabric</h4><ul><li>Explore end-to-end analytics with Microsoft Fabric</li><li>Data teams and Microsoft Fabric</li><li>Enable and use Microsoft Fabric</li><li>Knowledge Check</li></ul><h4>Get started with lakehouses in Microsoft Fabric</h4><ul><li>Explore the Microsoft Fabric Lakehouse</li><li>Work with Microsoft Fabric Lakehouses</li><li>Exercise - Create and ingest data with a Microsoft Fabric Lakehouse</li></ul><h4>Use Apache Spark in Microsoft Fabric</h4><ul><li>Prepare to use Apache Spark</li><li>Run Spark code</li><li>Work with data in a Spark dataframe</li><li>Work with data using Spark SQL</li><li>Visualize data in a Spark notebook</li><li>Exercise - Analyze data with Apache Spark</li></ul><h4>Work with Delta Lake Tables in Microsoft Fabric</h4><ul><li>Understand Delta Lake</li><li>Create delta tables</li><li>Work with delta tables in Spark</li><li>Use delta tables with streaming data</li><li>Exercise - Use delta tables in Apache Spark</li></ul><h4>Ingest Data with DataFlows Gen2 in Microsoft Fabric</h4><ul><li>Understand Dataflows (Gen2) in Microsoft Fabric</li><li>Explore Dataflows (Gen2) in Microsoft Fabric</li><li>Integrate Dataflows (Gen2) and Pipelines in Microsoft Fabric</li><li>Exercise - Create and use a Dataflow (Gen2) in Microsoft Fabric</li></ul></div>

Microsoft AZ-900

Apache Spark

Microsoft AZ-303

DP-601T00 Implementing a Lakehouse with Microsoft Fabric

Packt

Java

Sitecore

Data Analysis

Python

This course primarily focuses on explaining the concepts of Python and PySpark. It will help you enhance your data analysis skills using structured Spark DataFrames APIs.

Apache Spark 3 for Data Engineering and Analytics with Python

<strong>Learn the process to design and develop big data engineering projects using Apache Spark. This example-driven advanced-level course will help you understand real-time stream processing using Apache Spark and you can apply that knowledge to build real-time stream processing solutions.</strong>
        <p>Since its inception, Apache Spark has seen rapid adoption by enterprises across a wide range of industries. So, mastering Apache Spark opens a wide range of professional opportunities. If you are a software engineer or architect and want to design or build your own projects, then this is the right course for you.

This is a hands-on, example-driven, advanced course with demonstrations and coding sessions. This course will help you understand real-time stream processing using Apache Spark and later, you will be able to apply that knowledge to build real-time stream processing solutions.

This course covers everything from scratch, which involves installing Apache Spark and seeing how to set up and run Apache Kafka. Furthermore, it introduces stream processing and how to work with files and directories. You will also explore Kafka serialization and deserialization for Spark and how to work with Kafka AVRO Source.  And finally, the course wraps up with streaming Watermark and outer joints.

By the end of this course, you will be able to design and develop big data engineering projects. You will be able to create real-time stream processing applications with Apache Spark. This course will also help you further your growth in real-time stream processing.

All resources and code files are placed here: https://github.com/PacktPublishing/Spark-Streaming-In-Scala</p>
        <h2>What You Will Learn</h2><p>Create arbitrary streaming sinks<br>Explore Kafka Source and integrate Spark with Kafka<br>Learn state-less and state-full streaming transformations<br>Learn to handle memory problems with streaming joins<br>Learn to work with file streams<br>Explore windowing aggregates using Spark Stream</p>
        <h2>Audience</h2><p>This course is designed for software engineers and architects who aspire to develop big data engineering projects using Apache Spark. Also, if you are a programmer and developer who wants to grow and learn data engineering using Apache Spark, then this course is for you. Another group of people that can opt for this course are the managers and architects who might not directly work with Spark implementation but still work with the people who implement Apache Spark at the ground level.</p>
        <h2>Approach</h2><p>This is a comprehensive, hands-on, example-driven course, and it follows a working session-like approach. There is a combination of both theory and demonstration. The theory part explains all the concepts needed and then demonstrations to help you master real-time stream processing. It provides real-world examples to give you practical learning experience.</p>
        <h2>Key Features</h2><p>Deep dive into Spark structured streaming APIs and architecture * Discover streaming joins and aggregation * Explore real-time stream processing concepts</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Spark-Streaming-In-Scala</p>
        <h2>About the Author</h2><h3>Scholar Nest</h3><p>ScholarNest is a small team of people passionate about helping others learn and grow in their careers by bridging the gap between their existing and required skills.

Together, they have over 40+ years of experience in IT as a developer, architect, consultant, trainer, and mentor. They have worked with international software services organizations on various data-centric and Big Data projects.

It is a team of firm believers in lifelong continuous learning and skill development. To popularize the importance of continuous learning, they started publishing free training videos on their YouTube channel. They conceptualized the notion of continuous learning, creating a journal of our learning under the Learning Journal banner.</p>
        <h2>Course Outline</h2><h4>1. Before you start</h4><p></p><br><h4>2. Setup your Environment</h4><p></p><br><h4>3. Getting started with Spark Structured Streaming</h4><p></p><br><h4>4. Spark Streaming with Kafka</h4><p></p><br><h4>5. Windowing and Aggregates</h4><p></p><br><h4>6. Stream Processing and Joins</h4><p></p><br><h4>7. Keep Learning</h4><p></p>

Scala

Big Data

Kafka

Learn the process to design and develop big data engineering projects using Apache Spark. This example-driven advanced-level course will help you understand real-time stream processing using Apache Spark and you can apply that knowledge to build real-time stream processing solutions.

Real-Time Stream Processing Using Apache Spark 3 for Scala Developers

<strong>This course does not require any prior knowledge of Apache Spark or Hadoop. The author explains Spark architecture and fundamental concepts to help you come up to speed and grasp the content of this course.

The course will help you understand Spark programming and apply that knowledge to build data engineering solutions.</strong>
        <p>Apache Spark is a lightning-fast unified analytics engine for big data and machine learning. Since its release, Apache Spark has seen rapid adoption by enterprises across a wide range of industries. Internet powerhouses such as Netflix, Yahoo, and eBay have deployed Spark at a massive scale. It has quickly become the largest open-source community in big data. So, mastering Apache Spark opens a wide range of professional opportunities.

This course starts with an introduction to Apache Spark where you see what Apache Spark is in brief. Then, you will be installing and using Apache Spark. After that, you will look at the Spark execution model and architecture in detail. Next, you will learn the Spark programming model and developer experience. Following that, you will look at the Spark Structured API foundation, and Spark data sources and sinks. Then, you will explore Spark Data frame and dataset transformations along with aggregations in Apache Spark. Finally, you will look at the Spark Data frame joins in detail.

By the end of this course, you will understand Spark programming and apply that knowledge to build data engineering solutions.

All the resource files are uploaded on the GitHub repository at https://github.com/PacktPublishing/Spark-Programming-in-Scala-for-Beginners-with-Apache-Spark-3</p>
        <h2>What You Will Learn</h2><p>Learn Apache Spark and Spark architecture<br>Look at data engineering and data processing in Spark<br>Work with data sources and sinks<br>Work with data frames, datasets, and Spark SQL<br>Use IntelliJ IDEA for Spark development and debugging<br>Understand unit testing, managing application logs, and cluster deployment</p>
        <h2>Audience</h2><p>This course is designed for software engineers willing to develop a data engineering pipeline and application using Apache Spark. It is also for data architects and data engineers who are responsible for designing and building the organization's data-centric infrastructure. It will also be beneficial for the managers and architects who do not directly work with Spark implementation, and still, they work with the people who implement Apache Spark at the ground level.<br><br>Before proceeding with the course, you will need basic knowledge of the Scala programming language.</p>
        <h2>Approach</h2><p>This is a hands-on and well-balanced course with theoretical and practical content. The course is example-driven and follows a working session-like approach. The author will be taking a live coding approach and explaining all the concepts needed along the way. The section will have a summary video at the end to revise the learned concepts.</p>
        <h2>Key Features</h2><p>A comprehensive course designed for the beginner-level for Spark programming in Scala * Deep dive into Spark 3 architecture and data engineering * Complete tested source code and examples used on Apache Spark 3.0.0 open-source distribution from the author's end</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Spark-Programming-in-Scala-for-Beginners-with-Apache-Spark-3</p>
        <h2>About the Author</h2><h3>Scholar Nest</h3><p>ScholarNest is a small team of people passionate about helping others learn and grow in their careers by bridging the gap between their existing and required skills.

Together, they have over 40+ years of experience in IT as a developer, architect, consultant, trainer, and mentor. They have worked with international software services organizations on various data-centric and Big Data projects.

It is a team of firm believers in lifelong continuous learning and skill development. To popularize the importance of continuous learning, they started publishing free training videos on their YouTube channel. They conceptualized the notion of continuous learning, creating a journal of our learning under the Learning Journal banner.</p>
        <h2>Course Outline</h2><h4>1. Apache Spark Introduction</h4><p></p><br><h4>2. Installing and Using Apache Spark</h4><p></p><br><h4>3. Spark Execution Model and Architecture</h4><p></p><br><h4>4. Spark Programming Model and Developer Experience</h4><p></p><br><h4>5. Spark Structured API Foundation</h4><p></p><br><h4>6. Spark Data Sources and Sinks</h4><p></p><br><h4>7. Spark Dataframe and Dataset Transformations</h4><p></p><br><h4>8. Aggregations in Apache Spark</h4><p></p><br><h4>9. Spark Dataframe Joins</h4><p></p><br><h4>10. Keep Learning</h4><p></p>

Hadoop

This course does not require any prior knowledge of Apache Spark or Hadoop. The author explains Spark architecture and fundamental concepts to help you come up to speed and grasp the content of this course.

The course will help you understand Spark programming and apply that knowledge to build data engineering solutions.

Spark Programming in Scala for Beginners with Apache Spark 3

Data Visualization

Data Management

Discover Microsoft Fabric's architecture, master Data Engineering with OneLake and Spark, and elevate your skills in data warehousing and real-time processing. Compare SQL and KQL for better insights, and improve storytelling using Power BI. Finally, you will end with practical data science techniques and data management methods.

Microsoft Fabric Complete Guide - The Future of Data with Fabric

<strong>Get to grips with real-time stream processing using PySpark as well as Spark structured streaming and apply that knowledge to build stream processing solutions. This course is example-driven and follows a working session-like approach.</strong>
        <p>Take your first steps towards discovering, learning, and using Apache Spark 3.0. We will be taking a live coding approach in this carefully structured course and explaining all the core concepts needed along the way.

In this course, we will understand the real-time stream processing concepts, Spark structured streaming APIs, and architecture.

We will work with file streams, Kafka source, and integrating Spark with Kafka. Next, we will learn about state-less and state-full streaming transformations. Then cover windowing aggregates using Spark stream. Next, we will cover watermarking and state cleanup. After that, we will cover streaming joins and aggregation, handling memory problems with streaming joins. Finally, learn to create arbitrary streaming sinks.

By the end of this course, you will be able to create real-time stream processing applications using Apache Spark.

All the resources for the course are available at https://github.com/PacktPublishing/Real-time-stream-processing-using-Apache-Spark-3-for-Python-developers</p>
        <h2>What You Will Learn</h2><p>Explore state-less and state-full streaming transformations<br>Windowing aggregates using Spark stream<br>Learn Watermarking and state cleanup<br>Implement streaming joins and aggregations<br>Handling memory problems with streaming joins<br>Learn to create arbitrary streaming sinks</p>
        <h2>Audience</h2><p>This course is designed for software engineers and architects who are willing to design and develop big data engineering projects using Apache Spark. It is also designed for programmers and developers who are aspiring to grow and learn data engineering using Apache Spark.<br><br>For this course, you need to know Spark fundamentals and should be exposed to Spark Dataframe APIs. Also, you should know Kafka fundamentals and have a working knowledge of Apache Kafka. One should also have programming knowledge of Python programming.</p>
        <h2>Approach</h2><p>This course is example-driven and follows a working session-like approach. The course delivers live coding sessions and explains the concepts along the way.</p>
        <h2>Key Features</h2><p>Learn real-time stream processing concepts * Understand Spark structured streaming APIs and architecture * Work with file streams, Kafka source, and integrating Spark with Kafka</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Real-time-stream-processing-using-Apache-Spark-3-for-Python-developers</p>
        <h2>About the Author</h2><h3>Scholar Nest</h3><p>ScholarNest is a small team of people passionate about helping others learn and grow in their careers by bridging the gap between their existing and required skills.

Together, they have over 40+ years of experience in IT as a developer, architect, consultant, trainer, and mentor. They have worked with international software services organizations on various data-centric and Big Data projects.

It is a team of firm believers in lifelong continuous learning and skill development. To popularize the importance of continuous learning, they started publishing free training videos on their YouTube channel. They conceptualized the notion of continuous learning, creating a journal of our learning under the Learning Journal banner.</p>
        <h2>Course Outline</h2><h4>1. Before you Start</h4><p></p><br><h4>2. Setup your Environment</h4><p></p><br><h4>3. Getting started with Spark Structured Streaming</h4><p></p><br><h4>4. Spark Streaming with Kafka</h4><p></p><br><h4>5. Windowing and Aggregates</h4><p></p><br><h4>6. Stream Processing and Joins</h4><p></p><br><h4>7. Keep Learning</h4><p></p>

Data Processing

Get to grips with real-time stream processing using PySpark as well as Spark structured streaming and apply that knowledge to build stream processing solutions. This course is example-driven and follows a working session-like approach.

Real-Time Stream Processing Using Apache Spark 3 for Python Developers

<strong>A beginner's level course that will help you learn data engineering techniques for building metadata-driven frameworks with Azure data engineering tools such as Data Factory, Azure SQL, and others. You need not have any prior experience in Azure Data Factory to take up this course.</strong>
        <p>Building frameworks is now an industry norm and it has become an important skill to know how to visualize, design, plan, and implement data frameworks. The framework that we are going to build together is the Metadata-Driven Ingestion Framework. Metadata-driven frameworks allow a company to develop the system just once and it can be adopted and reused by various business clusters without the need for additional development, thus saving the business time and costs. Think of it as a plug-and-play system.

The first objective of the course is to onboard you onto the Azure Data Factory platform to help you assemble your first Azure Data Factory pipeline. Once you get a good grip on the Azure Data Factory development pattern, then it becomes easier to adopt the same pattern to onboard other sources and data sinks.

Once you are comfortable with building a basic Azure Data Factory pipeline, as a second objective, we then move on to building a fully-fledged and working metadata-driven framework to make the ingestion more dynamic; furthermore, we will build the framework in such a way that you can audit every batch orchestration and individual pipeline runs for business intelligence and operational monitoring.

By the end of this course, you will be able to design, implement, and get production-ready for data ingestion in Azure.

All the resource files are added to the GitHub repository at: https://github.com/PacktPublishing/Azure-Data-Factory-for-Beginners---Build-Data-Ingestion</p>
        <h2>What You Will Learn</h2><p>Learn about Azure Data Factory and Azure Blob Storage<br>Understand data engineering, data lake, and metadata-driven frameworks concepts<br>Look at the industry-based example of how to build ingestion frameworks<br>Learn dynamic Azure Data Factory pipelines and email notifications with logic apps<br>Study tracking of pipelines and batch runs<br>Look at version management with Azure DevOps</p>
        <h2>Audience</h2><p>This course is ideal for aspiring data engineers and developers that are curious about Azure Data Factory as an ETL alternative.<br><br>You will need a basic PC/laptop; no prior knowledge of Microsoft Azure is required.</p>
        <h2>Approach</h2><p>This course is comprehensive and well-structured into three parts: creating your first pipeline, metadata-driven ingestion, and event-driven ingestion. This highly practical course with real-life examples to learn how data engineers actually work on data analysis will leverage your learning further. The theoretical concepts are explained with beautiful animations to keep you engaged thoroughly.</p>
        <h2>Key Features</h2><p>A beginner-friendly and comprehensive course on designing and implementing Azure Data pipeline ingestion * Industry-based along with tips and tricks for production-ready data ingestion in an Azure project * The highly practical course along with the theoretical concepts animated for better interactivity</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Azure-Data-Factory-for-Beginners---Build-Data-Ingestion</p>
        <h2>About the Author</h2><h3>David Mngadi </h3><p>David Mngadi is a data management professional who is influenced by the power of data in our lives and has helped several companies become more data-driven to gain a competitive edge as well as meet the regulatory requirements. In the last 15 years, he has had the pleasure of designing and implementing data warehousing solutions in retail, telco, and banking industries, and recently in more big data lake-specific implementations. He is passionate about technology and teaching programming online.</p>
        <h2>Course Outline</h2><h4>1. Introduction - Build Your First Azure Data Pipeline</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to the Course</p><p style='margin: 0'>This video provides an introduction to the course and basics of ADF.</p></td></tr><tr><td style='padding: 15px;'><p>2. Introduction to ADF (Azure Data Factory)</p><p style='margin: 0'>This video provides an introduction to ADF (Azure Data Factory).</p></td></tr><tr><td style='padding: 15px;'><p>3. Requirements Discussion and Technical Architecture</p><p style='margin: 0'>This video talks about the requirements discussion and technical architecture.</p></td></tr><tr><td style='padding: 15px;'><p>4. Register a Free Azure Account</p><p style='margin: 0'>This video explains how to register a free Azure account.</p></td></tr><tr><td style='padding: 15px;'><p>5. Create a Data Factory Resource</p><p style='margin: 0'>This video helps you create a Data Factory resource.</p></td></tr><tr><td style='padding: 15px;'><p>6. Create a Storage Account and Upload Data</p><p style='margin: 0'>This video explains how to create a storage account and upload data.</p></td></tr><tr><td style='padding: 15px;'><p>7. Create Data Lake Gen 2 Storage Account</p><p style='margin: 0'>This video demonstrates how to create Data Lake Gen 2 storage account.</p></td></tr><tr><td style='padding: 15px;'><p>8. Download Storage Explorer</p><p style='margin: 0'>This video shows you how to download Storage Explorer.</p></td></tr><tr><td style='padding: 15px;'><p>9. Create Your First Azure Pipeline</p><p style='margin: 0'>This video talks about creating your first Azure pipeline.</p></td></tr><tr><td style='padding: 15px;'><p>10. Closing Remarks</p><p style='margin: 0'>This video concludes the section with the closing remarks.</p></td></tr></tbody></table><br><h4>2. Metadata-Driven Ingestion</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to Metadata-Driven Ingestion</p><p style='margin: 0'>This video provides an introduction to metadata-driven ingestion.</p></td></tr><tr><td style='padding: 15px;'><p>2. High-Level Plan</p><p style='margin: 0'>This video talks about the high-level plan you would be working on in this section.</p></td></tr><tr><td style='padding: 15px;'><p>3. Create Active Directory User</p><p style='margin: 0'>This video explains how to create an Active Directory user.</p></td></tr><tr><td style='padding: 15px;'><p>4. Assign the Contributor Role to the User</p><p style='margin: 0'>This video explains how to assign the contributor role to the user.</p></td></tr><tr><td style='padding: 15px;'><p>5. Disable Security Defaults</p><p style='margin: 0'>This video explains how to disable security defaults.</p></td></tr><tr><td style='padding: 15px;'><p>6. Creating the Metadata Database</p><p style='margin: 0'>This video talks about creating the metadata database.</p></td></tr><tr><td style='padding: 15px;'><p>7. Install Azure Data Studio</p><p style='margin: 0'>This video demonstrates installing Azure Data Studio.</p></td></tr><tr><td style='padding: 15px;'><p>8. Create Metadata Tables and Stored Procedures</p><p style='margin: 0'>This video explains creating metadata tables and stored procedures.</p></td></tr><tr><td style='padding: 15px;'><p>9. Reconfigure Existing Data Factory Artifacts</p><p style='margin: 0'>This video helps you reconfigure existing Data Factory artifacts.</p></td></tr><tr><td style='padding: 15px;'><p>10. Set Up Logic App to Handle Email Notifications</p><p style='margin: 0'>This video explains setting up logic app to handle email notifications.</p></td></tr><tr><td style='padding: 15px;'><p>11. Modify the Data Factory Pipeline to Send an Email Notification</p><p style='margin: 0'>This video shows how to modify the Data Factory pipeline to send an email notification.</p></td></tr><tr><td style='padding: 15px;'><p>12. Create Linked Service for Metadata Database and Email Dataset</p><p style='margin: 0'>This video demonstrates creating a linked service for metadata database and email dataset.</p></td></tr><tr><td style='padding: 15px;'><p>13. Create Utility Pipeline to Send Email Notifications</p><p style='margin: 0'>This video explains how to create a utility pipeline to send email notifications.</p></td></tr><tr><td style='padding: 15px;'><p>14. Explaining the Email Recipients Table</p><p style='margin: 0'>This video helps in explaining the 'Email recipients' table.</p></td></tr><tr><td style='padding: 15px;'><p>15. Explaining the Get Email Addresses Stored Procedure</p><p style='margin: 0'>This video explains the get email addresses stored procedure.</p></td></tr><tr><td style='padding: 15px;'><p>16. Modify Ingestion Pipeline to Use the Email Utility Pipeline</p><p style='margin: 0'>This video helps you modify the ingestion pipeline to use the email utility pipeline.</p></td></tr><tr><td style='padding: 15px;'><p>17. Tracking the Triggered Pipeline</p><p style='margin: 0'>This video lets you track the triggered pipeline.</p></td></tr><tr><td style='padding: 15px;'><p>18. Making the Email Notifications Dynamic</p><p style='margin: 0'>This video demonstrates making the email notifications dynamic.</p></td></tr><tr><td style='padding: 15px;'><p>19. Making Logging of Pipeline Information Dynamic</p><p style='margin: 0'>This video shows how to make the logging of pipeline information dynamic.</p></td></tr><tr><td style='padding: 15px;'><p>20. Add a New Way to Log the Main Ingestion Pipeline</p><p style='margin: 0'>This video explains how to add a new way to log the main ingestion pipeline.</p></td></tr><tr><td style='padding: 15px;'><p>21. Change the Logging of Pipelines to Send Fail Message Only</p><p style='margin: 0'>This video explains how to change the logging of pipelines to send a failure message only.</p></td></tr><tr><td style='padding: 15px;'><p>22. Creating Dynamic Datasets</p><p style='margin: 0'>This video talks about creating dynamic datasets.</p></td></tr><tr><td style='padding: 15px;'><p>23. Reading from Source to Target - Part 1</p><p style='margin: 0'>This is the first of the two-part video that helps in reading from source to target.</p></td></tr><tr><td style='padding: 15px;'><p>24. Reading from Source to Target - Part 2</p><p style='margin: 0'>This is the second of the two-part video that helps in reading from source to target.</p></td></tr><tr><td style='padding: 15px;'><p>25. Explaining the Source to Target Stored Procedure</p><p style='margin: 0'>This video helps in explaining the source to target stored procedure.</p></td></tr><tr><td style='padding: 15px;'><p>26. Add Orchestration Pipeline - Part 1</p><p style='margin: 0'>This is the first of the two-part video that explains how to add orchestration pipeline.</p></td></tr><tr><td style='padding: 15px;'><p>27. Add Orchestration Pipeline - Part 2</p><p style='margin: 0'>This is the second of the two-part video that explains how to add orchestration pipeline.</p></td></tr><tr><td style='padding: 15px;'><p>28. Fixing the Duplicating Batch Ingestions</p><p style='margin: 0'>This video explains fixing the duplicating batch ingestions.</p></td></tr><tr><td style='padding: 15px;'><p>29. Understanding the Pipeline Log and Related Tables</p><p style='margin: 0'>This video helps in understanding the pipeline log and related tables.</p></td></tr><tr><td style='padding: 15px;'><p>30. Understanding the GetBatch Stored Procedure</p><p style='margin: 0'>This video helps in understanding the GetBatch stored procedure.</p></td></tr><tr><td style='padding: 15px;'><p>31. Understanding the Set Batch Status and GetRunID</p><p style='margin: 0'>This video helps in understanding set batch status and GetRunID</p></td></tr><tr><td style='padding: 15px;'><p>32. Setting Up an Azure DevOps Git Repository</p><p style='margin: 0'>This video demonstrates setting up an Azure DevOps Git repository.</p></td></tr><tr><td style='padding: 15px;'><p>33. Publishing the Data Factory to Azure DevOps</p><p style='margin: 0'>This video helps in publishing the Data Factory to Azure DevOps.</p></td></tr><tr><td style='padding: 15px;'><p>34. Closing Remarks</p><p style='margin: 0'>This video concludes the section with the closing remarks.</p></td></tr></tbody></table><br><h4>3. Event-Driven Ingestion</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>This video provides an introduction to the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Read from Azure Storage Plan</p><p style='margin: 0'>This video explains how to read from Azure Storage Plan.</p></td></tr><tr><td style='padding: 15px;'><p>3. Create Finance Container and Upload Files</p><p style='margin: 0'>This video explains how to create finance container and upload files.</p></td></tr><tr><td style='padding: 15px;'><p>4. Create Source Dataset</p><p style='margin: 0'>This video helps in creating source dataset.</p></td></tr><tr><td style='padding: 15px;'><p>5. Write to Data Lake - Raw Plan</p><p style='margin: 0'>This video explains how to write to Data Lake - raw plan.</p></td></tr><tr><td style='padding: 15px;'><p>6. Create Finance Container and Directories</p><p style='margin: 0'>This video helps you create finance container and directories.</p></td></tr><tr><td style='padding: 15px;'><p>7. Create Sink Dataset</p><p style='margin: 0'>This video demonstrates creating sink dataset.</p></td></tr><tr><td style='padding: 15px;'><p>8. Data Factory Pipeline Plan</p><p style='margin: 0'>This video explains the Data Factory pipeline plan.</p></td></tr><tr><td style='padding: 15px;'><p>9. Create Data Factory and Read Metadata</p><p style='margin: 0'>This video explains creating Data Factory and reading metadata.</p></td></tr><tr><td style='padding: 15px;'><p>10. Add Filter by CSV</p><p style='margin: 0'>This video demonstrates how to add filter by CSV.</p></td></tr><tr><td style='padding: 15px;'><p>11. Add Dataset to Read Files</p><p style='margin: 0'>This video talks about adding dataset to read files.</p></td></tr><tr><td style='padding: 15px;'><p>12. Add the For Each CSV File Activity and Test Ingestion</p><p style='margin: 0'>This video explains how to add the For Each CSV file activity and test ingestion.</p></td></tr><tr><td style='padding: 15px;'><p>13. Adding the Event-Based Trigger Plan</p><p style='margin: 0'>This video demonstrates adding the event-based trigger plan.</p></td></tr><tr><td style='padding: 15px;'><p>14. Enable the Event Grid Provider</p><p style='margin: 0'>This video demonstrates enabling the event grid provider.</p></td></tr><tr><td style='padding: 15px;'><p>15. Delete File and Add Event-Based Trigger</p><p style='margin: 0'>This video demonstrates about deleting file and adding event-based trigger.</p></td></tr><tr><td style='padding: 15px;'><p>16. Create Event-Based Trigger</p><p style='margin: 0'>This video helps you create an event-based trigger.</p></td></tr><tr><td style='padding: 15px;'><p>17. Publish Code to Main Branch and Start Trigger</p><p style='margin: 0'>This video lets you publish the code to the main branch and start the trigger.</p></td></tr><tr><td style='padding: 15px;'><p>18. Trigger Event-Based Ingestion</p><p style='margin: 0'>This video helps you trigger event-based ingestion.</p></td></tr><tr><td style='padding: 15px;'><p>19. Closing Remarks</p><p style='margin: 0'>This video concludes the section with the closing remarks.</p></td></tr></tbody></table>

Microsoft Azure

A beginner's level course that will help you learn data engineering techniques for building metadata-driven frameworks with Azure data engineering tools such as Data Factory, Azure SQL, and others. You need not have any prior experience in Azure Data Factory to take up this course.

Azure Data Factory for Beginners - Build Data Ingestion

<div id="course-pills-1">Duration<p>4 Days</p><p>24 CPD hours</p>This course is intended for<p></p><p>The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure.</p><p></p><p></p><p>In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage.</p><p></p>Prerequisites<p></p><p>Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions.</p>  <li>AZ-900T00 Microsoft Azure Fundamentals</li>  <li>DP-900T00 Microsoft Azure Data Fundamentals</li><p></p></div><div id="course-pills-2"><h3>1 - Introduction to data engineering on Azure</h3> <ul> <li>What is data engineering</li> <li>Important data engineering concepts</li> <li>Data engineering in Microsoft Azure</li> </ul> <h3>2 - Introduction to Azure Data Lake Storage Gen2</h3> <ul> <li>Understand Azure Data Lake Storage Gen2</li> <li>Enable Azure Data Lake Storage Gen2 in Azure Storage</li> <li>Compare Azure Data Lake Store to Azure Blob storage</li> <li>Understand the stages for processing big data</li> <li>Use Azure Data Lake Storage Gen2 in data analytics workloads</li> </ul> <h3>3 - Introduction to Azure Synapse Analytics</h3> <ul> <li>What is Azure Synapse Analytics</li> <li>How Azure Synapse Analytics works</li> <li>When to use Azure Synapse Analytics</li> </ul> <h3>4 - Use Azure Synapse serverless SQL pool to query files in a data lake</h3> <ul> <li>Understand Azure Synapse serverless SQL pool capabilities and use cases</li> <li>Query files using a serverless SQL pool</li> <li>Create external database objects</li> </ul> <h3>5 - Use Azure Synapse serverless SQL pools to transform data in a data lake</h3> <ul> <li>Transform data files with the CREATE EXTERNAL TABLE AS SELECT statement</li> <li>Encapsulate data transformations in a stored procedure</li> <li>Include a data transformation stored procedure in a pipeline</li> </ul> <h3>6 - Create a lake database in Azure Synapse Analytics</h3> <ul> <li>Understand lake database concepts</li> <li>Explore database templates</li> <li>Create a lake database</li> <li>Use a lake database</li> </ul> <h3>7 - Analyze data with Apache Spark in Azure Synapse Analytics</h3> <ul> <li>Get to know Apache Spark</li> <li>Use Spark in Azure Synapse Analytics</li> <li>Analyze data with Spark</li> <li>Visualize data with Spark</li> </ul> <h3>8 - Transform data with Spark in Azure Synapse Analytics</h3> <ul> <li>Modify and save dataframes</li> <li>Partition data files</li> <li>Transform data with SQL</li> </ul> <h3>9 - Use Delta Lake in Azure Synapse Analytics</h3> <ul> <li>Understand Delta Lake</li> <li>Create Delta Lake tables</li> <li>Create catalog tables</li> <li>Use Delta Lake with streaming data</li> <li>Use Delta Lake in a SQL pool</li> </ul> <h3>10 - Analyze data in a relational data warehouse</h3> <ul> <li>Design a data warehouse schema</li> <li>Create data warehouse tables</li> <li>Load data warehouse tables</li> <li>Query a data warehouse</li> </ul> <h3>11 - Load data into a relational data warehouse</h3> <ul> <li>Load staging tables</li> <li>Load dimension tables</li> <li>Load time dimension tables</li> <li>Load slowly changing dimensions</li> <li>Load fact tables</li> <li>Perform post load optimization</li> </ul> <h3>12 - Build a data pipeline in Azure Synapse Analytics</h3> <ul> <li>Understand pipelines in Azure Synapse Analytics</li> <li>Create a pipeline in Azure Synapse Studio</li> <li>Define data flows</li> <li>Run a pipeline</li> </ul> <h3>13 - Use Spark Notebooks in an Azure Synapse Pipeline</h3> <ul> <li>Understand Synapse Notebooks and Pipelines</li> <li>Use a Synapse notebook activity in a pipeline</li> <li>Use parameters in a notebook</li> </ul> <h3>14 - Plan hybrid transactional and analytical processing using Azure Synapse Analytics</h3> <ul> <li>Understand hybrid transactional and analytical processing patterns</li> <li>Describe Azure Synapse Link</li> </ul> <h3>15 - Implement Azure Synapse Link with Azure Cosmos DB</h3> <ul> <li>Enable Cosmos DB account to use Azure Synapse Link</li> <li>Create an analytical store enabled container</li> <li>Create a linked service for Cosmos DB</li> <li>Query Cosmos DB data with Spark</li> <li>Query Cosmos DB with Synapse SQL</li> </ul> <h3>16 - Implement Azure Synapse Link for SQL</h3> <ul> <li>What is Azure Synapse Link for SQL?</li> <li>Configure Azure Synapse Link for Azure SQL Database</li> <li>Configure Azure Synapse Link for SQL Server 2022</li> </ul> <h3>17 - Get started with Azure Stream Analytics</h3> <ul> <li>Understand data streams</li> <li>Understand event processing</li> <li>Understand window functions</li> </ul> <h3>18 - Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics</h3> <ul> <li>Stream ingestion scenarios</li> <li>Configure inputs and outputs</li> <li>Define a query to select, filter, and aggregate data</li> <li>Run a job to ingest data</li> </ul> <h3>19 - Visualize real-time data with Azure Stream Analytics and Power BI</h3> <ul> <li>Use a Power BI output in Azure Stream Analytics</li> <li>Create a query for real-time visualization</li> <li>Create real-time data visualizations in Power BI</li> </ul> <h3>20 - Introduction to Microsoft Purview</h3> <ul> <li>What is Microsoft Purview?</li> <li>How Microsoft Purview works</li> <li>When to use Microsoft Purview</li> </ul> <h3>21 - Integrate Microsoft Purview and Azure Synapse Analytics</h3> <ul> <li>Catalog Azure Synapse Analytics data assets in Microsoft Purview</li> <li>Connect Microsoft Purview to an Azure Synapse Analytics workspace</li> <li>Search a Purview catalog in Synapse Studio</li> <li>Track data lineage in pipelines</li> </ul> <h3>22 - Explore Azure Databricks</h3> <ul> <li>Get started with Azure Databricks</li> <li>Identify Azure Databricks workloads</li> <li>Understand key concepts</li> </ul> <h3>23 - Use Apache Spark in Azure Databricks</h3> <ul> <li>Get to know Spark</li> <li>Create a Spark cluster</li> <li>Use Spark in notebooks</li> <li>Use Spark to work with data files</li> <li>Visualize data</li> </ul> <h3>24 - Run Azure Databricks Notebooks with Azure Data Factory</h3> <ul> <li>Understand Azure Databricks notebooks and pipelines</li> <li>Create a linked service for Azure Databricks</li> <li>Use a Notebook activity in a pipeline</li> <li>Use parameters in a notebook</li> </ul></div><div id="course-pills-3"><h4>Additional course details:</h4><br /><p>Nexus Humans DP-203T00 Data Engineering on Microsoft Azure training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. </p><p></p> This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. <p></p>Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.  <p></p>While we feel this is the best course for the DP-203T00 Data Engineering on Microsoft Azure course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.  <p></p>Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.<p></p></div>

Microsoft AZ-104

Microsoft AZ-700

DP-203T00 Data Engineering on Microsoft Azure

<p><strong>24 Hour Flash Deal **25-in-1 </strong><strong>Data Engineering Advanced Diploma </strong><strong>Mega Bundle**</strong></p><p><strong> </strong><strong>Data Engineering Advanced Diploma </strong><strong>Enrolment Gifts  **FREE PDF Certificate**FREE PDF Transcript ** FREE Exam** FREE Student ID ** Lifetime Access **FREE Enrolment Letter **</strong></p><p>Take the initial steps toward a successful long-term career by studying the <strong>Data Engineering Advanced Diploma</strong> package online with <strong>Studyhub </strong>through our online learning platform. The Data Engineering Advanced Diploma bundle can help you improve your CV, wow potential employers, and differentiate yourself from the mass.</p><p>This <strong>Data Engineering Advanced Diploma </strong>course provides complete 360-degree training on Data Engineering Advanced Diploma. You'll get not one, not two, not three, but <strong>twenty-five </strong>Data Engineering Advanced Diploma courses included in this course. Plus Studyhub's signature <strong>Forever Access</strong> is given as always, meaning these Data Engineering Advanced Diploma courses are yours for as long as you want them once you enrol in this course</p><p><strong>This Data Engineering Advanced Diploma Bundle consists the following career oriented courses:</strong></p><ul><li>Course 01: Data Analysis</li><li>Course 02: Data Science &amp; Machine Learning with R</li><li>Course 03: Data Analytics with Tableau</li><li>Course 04: SQL Programming</li><li>Course 05: Excel Pivot Tables, Pivot Charts, Slicers, and Timelines</li><li>Course 06: Data Analytics</li><li>Course 07: Python Data Science with Numpy, Pandas and Matplotlib</li><li>Course 08: Google Analytics</li><li>Course 09: Business Intelligence and Data Mining</li><li>Course 10: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query</li><li>Course 11: JavaScript Functions</li><li>Course 12: Data Protection and Data Security (GDPR) Training Certification</li><li>Course 13: GDPR Training</li><li>Course 14: Diploma in Python Programming</li><li>Course 15: Data Center Training Essentials: General Introduction</li><li>Course 16: Quick Data Science Approach from Scratch</li><li>Course 17: Diploma in Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li>Course 18: Master JavaScript with Data Visualization</li><li>Course 19: Data Analysis and Forecasting in Excel</li><li>Course 20: AWS Certified Solutions Architect Associate Preparation</li><li>Course 21: Statistical Analysis Course</li><li>Course 22: SQL for Data Science, Data Analytics and Data Visualization</li><li>Course 23: Learn MySQL from Scratch for Data Science and Analytics</li><li>Course 24: Data Analysis &amp; Forecasting</li><li>Course 25: Data Structure</li></ul> <p>The <strong>Data Engineering Advanced Diploma </strong>course has been prepared by focusing largely on Data Engineering Advanced Diploma career readiness. It has been designed by our Data Engineering Advanced Diploma specialists in a manner that you will be likely to find yourself head and shoulders above the others. For better learning, one to one assistance will also be provided if it's required by any learners.</p><p>The Data Engineering Advanced Diploma Bundle is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Data Engineering Advanced Diploma bundle course has been created with <strong>twenty-five </strong>premium courses to provide our learners with the best learning experience possible to increase their understanding of their chosen field.</p><p>This Data Engineering Advanced Diploma Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into Data Engineering Advanced Diploma Elementary modules, allowing our students to grasp each lesson quickly.</p><p>The Data Engineering Advanced Diploma course is self-paced and can be taken from the comfort of your home, office, or on the go! With our Student ID card you will get discounts on things like music, food, travel and clothes etc.</p><p><strong>In this exclusive </strong><strong>Data Engineering Advanced Diploma </strong><strong>bundle, you really hit the jackpot. Here's what you get:</strong></p><ul><li>Step by step Data Engineering Advanced Diploma lessons</li><li>One to one assistance from Data Engineering Advanced Diplomaprofessionals if you need it</li><li>Innovative exams to test your knowledge after the Data Engineering Advanced Diplomacourse</li><li>24/7 customer support should you encounter any hiccups</li><li>Top-class learning portal</li><li>Unlimited lifetime access to all twenty-five Data Engineering Advanced Diploma courses</li><li>Digital Certificate, Transcript and student ID are all included in the price</li><li>PDF certificate immediately after passing</li><li>Original copies of your Data Engineering Advanced Diploma certificate and transcript on the next working day</li><li>Easily learn the Data Engineering Advanced Diploma skills and knowledge you want from the comfort of your home</li></ul> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        250 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div> <h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>This <strong>Data Engineering Advanced Diploma </strong>training is suitable for -</p><ul><li>Students</li><li>Recent graduates</li><li>Job Seekers</li><li>Individuals who are already employed in the relevant sectors and wish to enhance their knowledge and expertise in Data Engineering Advanced Diploma</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>To participate in this <strong>Data Engineering Advanced Diploma </strong>course, all you need is -</p><ul><li>A smart device</li><li>A secure internet connection</li><li>And a keen interest in Data Engineering Advanced Diploma</li></ul>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>You will be able to kickstart your <strong>Data Engineering Advanced Diploma </strong>career because this course includes various courses as a bonus. This Data Engineering Advanced Diploma is an excellent opportunity for you to learn multiple skills from the convenience of your own home and explore Data Engineering Advanced Diploma career opportunities.</p>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
            <div><ul><li>CPD Accredited e-Certificate - Free</li><li>CPD Accredited Hardcopy Certificate - Free</li><li>Enrolment Letter - Free</li><li>Student ID Card - Free</li></ul></div>

                        </div>

Studyhub UK

Diploma in Education & Training (DET)

European Computer Driving Licence (ECDL)

Diploma in Management Studies (DMS)

Diploma in Professional Studies (DPS)

Nursing Diploma

Data Engineering Advanced Diploma - CPD Certified

<p><strong>24 Hours Left! Don't Let Winter Sale Slip Away - Enrol Now!</strong></p><p><strong>With over 100,000 civil engineers in the UK, the demand for data-savvy professionals is high. According to a recent study, 72% of UK civil engineering firms are investing in data analytics to enhance decision-making processes, with data engineering experiencing a 40% year-on-year growth.</strong></p><p>This surge outpaces other tech sectors, highlighting the critical role of data engineers in big data and advanced analytics. This Data Engineering bundle empowers you to capitalise on this growing trend, equipping you with the proficiency to extract valuable insights from vast datasets, optimise project planning, and enhance overall efficiency.</p><p>Embark on a transformative journey with our Data Engineering Bundle, thoroughly crafted to bridge the skill gap in one of the UK's fastest-growing job markets. Our bundle offers a comprehensive exploration into the world of data, equipping you with the analytical prowess to harness, process, and visualise data effectively. From mastering SQL programming to delving into the complexities of machine learning with R, this bundle is your gateway to becoming a data engineering maestro.</p><p>In today's data-driven landscape, possessing a robust set of analytical skills is no longer a luxury but a necessity. With an emphasis on Data engineering, our courses are designed to foster a deep understanding of data analytics, visualisation, and mining, ensuring you can convert raw data into strategic insights that propel business decisions.</p><p>Seize the opportunity to be at the helm of innovation and become the architect of tomorrow's data landscape with our Data Engineering Bundle. Join us now!</p><p><strong>Courses are Included in This Data Engineering Bundle:</strong></p><ul><li><strong> Course 01: </strong>Introduction to Data Analysis</li><li><strong> Course 02: </strong>Data Science &amp; Machine Learning with R</li><li><strong> Course 03: </strong>Data Analytics with Tableau</li><li><strong> Course 04: </strong>SQL Programming Masterclass</li><li><strong> Course 05: </strong>Excel Pivot table for Data analytics</li><li><strong> Course 06: </strong>Data analytics with Excel</li><li><strong> Course 07: </strong>Python for Data Analysis</li><li><strong> Course 08: </strong>Basic Google Data Studio</li><li><strong> Course 09: </strong>Business Intelligence and Data Mining Masterclass</li><li><strong> Course 10: </strong>Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query</li><li><strong> Course 11: </strong>JavaScript Functions for Data Analyst</li><li><strong> Course 12: </strong>GDPR Data Protection Level 5</li><li><strong> Course 13: </strong>GDPR Training</li><li><strong> Course 14: </strong>Learn Programming with Python</li><li><strong> Course 15: </strong>Data Center Training Essentials: General Introduction</li><li><strong> Course 16: </strong>Quick Data Science Approach from Scratch</li><li><strong> Course 17: </strong>Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li><strong> Course 18: </strong>Master JavaScript with Data Visualization</li><li><strong> Course 19: </strong>Excel Data Tools and Data Management</li><li><strong> Course 20: </strong>Cloud Computing Essentials for Data Analysis</li></ul><p><strong>Learning Outcomes of Data Engineering Bundle:</strong></p><ul><li>Gain proficiency in SQL for complex database management and analytics tasks.</li><li>Master R for data science and machine learning applications in various industries.</li><li>Develop advanced Excel skills, including data analytics and pivot table expertise.</li><li>Acquire hands-on experience with Tableau for effective data visualisation.</li><li>Learn Python programming essentials for data analysis and engineering solutions.</li><li>Understand Google Data Studio to create dynamic reports and dashboards.</li></ul><p><strong>Why Choose Our Data Engineering Course?</strong></p><ul><li>FREE Data Engineering certificate accredited</li><li>Get a free student ID card with Data Engineering Training</li><li>Get instant access to this Data Engineering course.</li><li>Learn Data Engineering from anywhere in the world</li><li>The Data Engineering is affordable and simple to understand</li><li>The Data Engineering is an entirely online, interactive lesson with voiceover audio</li><li>Lifetime access to the Data Engineering course materials</li><li>The Data Engineering comes with 24/7 tutor support</li></ul> <p><strong>Start your learning journey straightaway with our Data Engineering Bundle!</strong></p><p>This Data Engineering bundle will equip you with the skills and knowledge to become a data-savvy civil engineer. You will learn how to collect, analyze, and interpret data to improve infrastructure projects and processes. This Data Engineering bundle includes courses on data analysis, data science, machine learning, SQL programming, Excel pivot tables, Excel data analytics, Python for data analysis, Google Data Studio, business intelligence, data mining, GDPR data protection, JavaScript functions for data analysts, and Python programming.</p><p><strong>Assessment Process of Data Engineering</strong></p><p>Once you have completed all the courses in the Data Engineering bundle, you can assess your skills and knowledge with an optional assignment. Our expert trainers will assess your assignment and give you feedback afterwards.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        200 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div> <h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>This Data Engineering bundle is suitable for everyone. Also, our Data Engineering Bundle is perfect for:</p><ul><li>Aspiring data engineers</li><li>Business intelligence analysts</li><li>Data-driven marketers</li><li>IT professionals</li><li>Statistics enthusiasts</li><li>Career changers</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You will not need any prior background or expertise in the Data Engineering Bundle.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This Data Engineering bundle will allow you to kickstart or take your career to the next stage in the related sector such as:</p><ul><li><strong>Data Analyst</strong></li><li><strong>BI Developer</strong></li><li><strong>ML Engineer</strong></li><li><strong>Data Scientist</strong></li><li><strong>Database Administrator</strong></li><li><strong>Data Strategist</strong></li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited Digital Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>CPD Accredited Hard Copy Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div><p>If you are an <strong>international student</strong>, then you have to pay an additional <strong>10 GBP</strong> for each certificate as an international delivery charge.</p></div>

                        </div>

Academy for Health and Fitness

Data Engineering - CPD Certified

<p>If you aim to enhance your Data Engineering skills, our comprehensive Data Engineering course is perfect for you. Designed for success, this Data Engineering course covers everything from basics to advanced topics in Data Engineering.</p><p>Each lesson in this Data Engineering course is crafted for easy understanding, enabling you to become proficient in Data Engineering. Whether you are a beginner or looking to sharpen your existing skills, this Data Engineering is the ideal choice.</p><p>With our Data Engineering exclusive bundle, you will get<strong> a PDF Certificate, PDF Transcript and Digital Student ID Card (worth £50) Absolutely FREE. </strong></p><p><strong>Courses are Included in This Data Engineering Bundle:</strong></p><ul><li><strong>Course 01: </strong>Diploma in Data Analysis Fundamentals</li><li><strong>Course 02: </strong>Python for Data Analysis</li><li><strong>Course 03: </strong>Data Analytics with Tableau</li><li><strong>Course 04: </strong>SQL Masterclass: SQL For Data Analytics</li><li><strong>Course 05: </strong>Basic Google Data Studio</li><li><strong>Course 06: </strong>Data Analysis and Forecasting in Excel</li></ul><p><strong>Why Choose Our Data Engineering Course?</strong></p><ul><li>FREE Data Engineering certificate accredited</li><li>Get a free student ID card with Data Engineering Training</li><li>Get instant access to this Data Engineering course.</li><li>Learn Data Engineering from anywhere in the world</li><li>The Data Engineering is affordable and simple to understand</li><li>The Data Engineering is an entirely online, interactive lesson with voiceover audio</li><li>Lifetime access to the Data Engineering course materials</li><li>The Data Engineering comes with 24/7 tutor support</li></ul><p>So enrol now in this Data Engineering Today to advance your career!</p> <p>Start your learning journey straightaway!</p><p>This Data Engineering's curriculum has been designed by Data Engineering experts with years of Data Engineering experience behind them. The Data Engineering course is extremely dynamic and well-paced to help you understand Data Engineering with ease. You'll discover how to master the Data Engineering skill while exploring relevant and essential topics.</p><p><strong>Assessment Process</strong></p><p>Once you have completed all the courses in the Data Engineering bundle, you can assess your skills and knowledge with an optional assignment. Our expert trainers will assess your assignment and give you feedback afterwards.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        60 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div> <h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>This Data Engineering bundle is suitable for everyone.</p>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You will not need any prior background or expertise.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This Data Engineering bundle will allow you to kickstart or take your career in the related sector to the next stage.</p>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited  Digital certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>CPD Accredited   Hard copy certificate</h4>
        <p>
            Hard copy certificate -
            £29
        </p>
            <div><p>If you are an international student, you will be required to pay an additional fee of <strong>10 GBP</strong> for international delivery, and <strong>4.99 GBP</strong> for delivery within the UK, for each certificate</p></div>

                        </div>

Certificate in Further Education & Training (Cert Ed)

Certified in Data Protection (CDP)

Continuous Professional Development (CPD)

Data Engineering (Online) - CPD Certified

<div id="course-pills-1">Duration<p>4 Days</p><p>24 CPD hours</p>This course is intended for<p></p><p>This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.</p><p></p>Overview<p>Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.</p><p></p><p>Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow.</p><p></p>Prerequisites<p></p><li>Creating cloud resources in Microsoft Azure.</li>  <li>Using Python to explore and visualize data.</li>  <li>Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow.</li>  <li>Working with containers</li>  <li>AI-900T00: Microsoft Azure AI Fundamentals is recommended, or the equivalent experience.</li><p></p></div><div id="course-pills-2"><h3>1 - Design a data ingestion strategy for machine learning projects</h3> <ul> <li>Identify your data source and format</li> <li>Choose how to serve data to machine learning workflows</li> <li>Design a data ingestion solution</li> </ul> <h3>2 - Design a machine learning model training solution</h3> <ul> <li>Identify machine learning tasks</li> <li>Choose a service to train a machine learning model</li> <li>Decide between compute options</li> </ul> <h3>3 - Design a model deployment solution</h3> <ul> <li>Understand how model will be consumed</li> <li>Decide on real-time or batch deployment</li> </ul> <h3>4 - Design a machine learning operations solution</h3> <ul> <li>Explore an MLOps architecture</li> <li>Design for monitoring</li> <li>Design for retraining</li> </ul> <h3>5 - Explore Azure Machine Learning workspace resources and assets</h3> <ul> <li>Create an Azure Machine Learning workspace</li> <li>Identify Azure Machine Learning resources</li> <li>Identify Azure Machine Learning assets</li> <li>Train models in the workspace</li> </ul> <h3>6 - Explore developer tools for workspace interaction</h3> <ul> <li>Explore the studio</li> <li>Explore the Python SDK</li> <li>Explore the CLI</li> </ul> <h3>7 - Make data available in Azure Machine Learning</h3> <ul> <li>Understand URIs</li> <li>Create a datastore</li> <li>Create a data asset</li> </ul> <h3>8 - Work with compute targets in Azure Machine Learning</h3> <ul> <li>Choose the appropriate compute target</li> <li>Create and use a compute instance</li> <li>Create and use a compute cluster</li> </ul> <h3>9 - Work with environments in Azure Machine Learning</h3> <ul> <li>Understand environments</li> <li>Explore and use curated environments</li> <li>Create and use custom environments</li> </ul> <h3>10 - Find the best classification model with Automated Machine Learning</h3> <ul> <li>Preprocess data and configure featurization</li> <li>Run an Automated Machine Learning experiment</li> <li>Evaluate and compare models</li> </ul> <h3>11 - Track model training in Jupyter notebooks with MLflow</h3> <ul> <li>Configure MLflow for model tracking in notebooks</li> <li>Train and track models in notebooks</li> </ul> <h3>12 - Run a training script as a command job in Azure Machine Learning</h3> <ul> <li>Convert a notebook to a script</li> <li>Run a script as a command job</li> <li>Use parameters in a command job</li> </ul> <h3>13 - Track model training with MLflow in jobs</h3> <ul> <li>Track metrics with MLflow</li> <li>View metrics and evaluate models</li> </ul> <h3>14 - Perform hyperparameter tuning with Azure Machine Learning</h3> <ul> <li>Define a search space</li> <li>Configure a sampling method</li> <li>Configure early termination</li> <li>Use a sweep job for hyperparameter tuning</li> </ul> <h3>15 - Run pipelines in Azure Machine Learning</h3> <ul> <li>Create components</li> <li>Create a pipeline</li> <li>Run a pipeline job</li> </ul> <h3>16 - Register an MLflow model in Azure Machine Learning</h3> <ul> <li>Log models with MLflow</li> <li>Understand the MLflow model format</li> <li>Register an MLflow model</li> </ul> <h3>17 - Create and explore the Responsible AI dashboard for a model in Azure Machine Learning</h3> <ul> <li>Understand Responsible AI</li> <li>Create the Responsible AI dashboard</li> <li>Evaluate the Responsible AI dashboard</li> </ul> <h3>18 - Deploy a model to a managed online endpoint</h3> <ul> <li>Explore managed online endpoints</li> <li>Deploy your MLflow model to a managed online endpoint</li> <li>Deploy a model to a managed online endpoint</li> <li>Test managed online endpoints</li> </ul> <h3>19 - Deploy a model to a batch endpoint</h3> <ul> <li>Understand and create batch endpoints</li> <li>Deploy your MLflow model to a batch endpoint</li> <li>Deploy a custom model to a batch endpoint</li> <li>Invoke and troubleshoot batch endpoints</li> </ul></div>

Azure Machine Learning

DP-100T01 Designing and Implementing a Data Science Solution on Azure

<p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(15, 21, 26);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">✿ 17</strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">&nbsp;in 1 "Data Engineering: Big Data &amp; Google Cloud Architect" CPD Certified Diploma ✿</strong></p><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);">Are you interested in pursuing a career in data analysis? Do you want to gain the skills and knowledge necessary to excel in the field of data analytics? Look no further! Our comprehensive&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Engineering: Big Data &amp; Google Cloud Architect Diploma</strong>&nbsp;bundle offers a thorough overview of the essential concepts, techniques, and tools required to succeed in this exciting and rapidly growing field.</p><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Engineering: Big Data &amp; Google Cloud Architect Diploma training offers :</strong></p><ul style="color: rgb(15, 21, 26); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">17&nbsp;</strong>Free PDF Certificates</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Lifetime&nbsp;</strong>Access</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">24/7</strong>&nbsp;Learner Support</li></ul><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);">Enter into the world of data engineering with our "<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Engineering: Big Data &amp; Google Cloud Architect</strong>" bundle. Designed for both beginner and those with foundational knowledge, this Data Engineering: Big Data &amp; Google Cloud Architect bundle will elevate your understanding of big data and cloud architecture. With the proliferation of data in today&#39;s digital landscape, mastering these skills is crucial for anyone aiming to make a significant impact in the tech industry.</p><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);">The&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Engineering: Big Data &amp; Google Cloud Architect&nbsp;</strong>diploma training provides a comprehensive curriculum that covers everything from the basics of data engineering to advanced topics in Google Cloud, Big Query, Data Structures, SQL/MySQL Database etc. Through engaging modules, you&#39;ll gain insight into the intricacies of data processing, storage solutions, and cloud infrastructure.</p><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);">By completing this&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Engineering: Big Data &amp; Google Cloud Architect&nbsp;</strong>training, you&#39;ll be equipped with the knowledge needed to architect robust data solutions using Google Cloud. You&#39;ll understand the principles behind big data management and how to apply them in real-world contexts. Whether you&#39;re looking to enhance your career prospects or pivot into a new field, this&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Engineering: Big Data &amp; Google Cloud Architect</strong>&nbsp;bundle offers the tools and understanding required to succeed in the ever-evolving data engineering landscape.</p><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Engineering: Big Data &amp; Google Cloud Architect Bundle Consists the Following Courses:</strong></p><ol style="color: rgb(15, 21, 26); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><li fr-original-style="" style="box-sizing: border-box;">Data Engineering: Google Big Query &amp; Google Cloud</li><li fr-original-style="" style="box-sizing: border-box;">Mastering MySQL Database Development</li><li fr-original-style="" style="box-sizing: border-box;">Data Analytics with Tableau</li><li fr-original-style="" style="box-sizing: border-box;">Data Structures : Easy to Advanced</li><li fr-original-style="" style="box-sizing: border-box;">JavaScript for Data Structures</li><li fr-original-style="" style="box-sizing: border-box;">SQL Complete Training</li><li fr-original-style="" style="box-sizing: border-box;">Microsoft SQL Queries</li><li fr-original-style="" style="box-sizing: border-box;">Python Programming Complete Training</li><li fr-original-style="" style="box-sizing: border-box;">Python Data Science - For Beginners</li><li fr-original-style="" style="box-sizing: border-box;">Machine Learning in Flutter: Complete Guide</li><li fr-original-style="" style="box-sizing: border-box;">Data Science &amp; Machine Learning with R Complete Training</li><li fr-original-style="" style="box-sizing: border-box;">Python: Higher Order Functions</li><li fr-original-style="" style="box-sizing: border-box;">Linux File System</li><li fr-original-style="" style="box-sizing: border-box;">LabVIEW &ndash; Step By Step Beginners Guide</li><li fr-original-style="" style="box-sizing: border-box;">SQL NoSQL Big Data and Hadoop All in One Course</li><li fr-original-style="" style="box-sizing: border-box;">Basic Data Analysis Training</li><li fr-original-style="" style="box-sizing: border-box;">Data Analysis: Getting Results with PowerBI</li></ol><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Learning Outcomes of Data Engineering: Big Data &amp; Google Cloud Architect Diploma</strong></p><ul style="color: rgb(15, 21, 26); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><li fr-original-style="" style="box-sizing: border-box;">Understand the fundamentals of data engineering.</li><li fr-original-style="" style="box-sizing: border-box;">Gain proficiency in Google Cloud Platform services.</li><li fr-original-style="" style="box-sizing: border-box;">Master techniques for big data processing.</li><li fr-original-style="" style="box-sizing: border-box;">Learn to design scalable data architecture.</li><li fr-original-style="" style="box-sizing: border-box;">Implement effective data storage solutions.</li><li fr-original-style="" style="box-sizing: border-box;">Analyse and optimise data workflows.</li><li fr-original-style="" style="box-sizing: border-box;">Develop skills in managing cloud-based data systems.</li><li fr-original-style="" style="box-sizing: border-box;">Comprehend security measures for data protection.</li><li fr-original-style="" style="box-sizing: border-box;">Explore methods for data integration and migration.</li><li fr-original-style="" style="box-sizing: border-box;">Apply knowledge to design and implement data solutions.</li></ul><h2 fr-original-style=" color: rgb(15, 21, 26);" style="color: rgb(15, 21, 26); box-sizing: border-box;" id="isPasted">Certificates</h2><div fr-original-style=" color: rgb(15, 21, 26);" style="color: rgb(15, 21, 26); box-sizing: border-box;"><p fr-original-style=" color: var(--text);" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Digital Certificate</strong></p><p fr-original-style=" color: var(--text);" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This bundle comes with a free <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">CPD Accredited PDF Copy certificate+ Transcript&nbsp;</strong>(according to the Learner&#39;s Choice). For additional courses, it costs <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">&pound;14.99</strong> per copy.</p><p fr-original-style=" color: var(--text);" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Hard Copy Certificate</strong></p><p fr-original-style=" color: var(--text);" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Get <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">CPD Accredited Hard Copy certificate</strong> for <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">&pound;19.99</strong> per copy. The delivery fee for the Hard Copy certificate, however, is free for UK residents, whereas it costs <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">&pound;10</strong> for international students as delivery charge.</p><section style="color: rgb(15, 21, 26); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(15, 21, 26);"><h2 style="color: var(--bs-heading-color); box-sizing: border-box;" fr-original-style=" color: var(--bs-heading-color);">Who is this course for?</h2><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Engineering: Big Data &amp; Google Cloud Architect</strong>&nbsp;diploma training is open to everyone. Specially designed for:</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Aspiring data engineers.</li><li fr-original-style="" style="box-sizing: border-box;">IT professionals seeking to specialise in data engineering.</li><li fr-original-style="" style="box-sizing: border-box;">Individuals interested in big data technologies.</li><li fr-original-style="" style="box-sizing: border-box;">Those aiming to understand Google Cloud architecture.</li><li fr-original-style="" style="box-sizing: border-box;">Career changers looking to enter the tech industry.</li></ul></section><section style="color: rgb(15, 21, 26); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><h2 style="color: var(--bs-heading-color); box-sizing: border-box;" fr-original-style=" color: var(--bs-heading-color);">Requirements</h2><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">For this&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Engineering: Big Data &amp; Google Cloud Architect</strong>&nbsp;bundle, you don&#39;t need any formal qualifications.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Take your time to finish this Data Science Engineering: Data Analytics &amp; Database Management training, there is no deadline for the bundle.</p></section><section style="color: rgb(15, 21, 26); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><h2 style="color: var(--bs-heading-color); box-sizing: border-box;" fr-original-style=" color: var(--bs-heading-color);">Career path</h2><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Engineering: Big Data &amp; Google Cloud Architect</strong>&nbsp;training can lead you towards successful careers in these related fields. Such as:</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Data Engineer: &pound;40,000 - &pound;70,000</li><li fr-original-style="" style="box-sizing: border-box;">Cloud Solutions Architect: &pound;50,000 - &pound;90,000</li><li fr-original-style="" style="box-sizing: border-box;">Big Data Analyst: &pound;35,000 - &pound;60,000</li><li fr-original-style="" style="box-sizing: border-box;">Data Architect: &pound;60,000 - &pound;100,000</li><li fr-original-style="" style="box-sizing: border-box;">Business Intelligence Developer: &pound;40,000 - &pound;75,000</li><li fr-original-style="" style="box-sizing: border-box;">Machine Learning Engineer: &pound;50,000 - &pound;85,000</li></ul></section></div>

Skill Up

CPD Certified | 17-in-1 Diploma Bundle | 170 CPD Points | Free PDF & Transcript Certificate | Lifetime Access


Data Engineering: Big Data & Google Cloud Architect Diploma - CPD Certified


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					<div><p>Gain the solid skills and knowledge to kickstart a successful career and learn from the experts with this step-by-step Data Engineering : Google BigQuery &amp; Google Cloud training course. This Data Engineering : Google BigQuery &amp; Google Cloud course for Consistent Profits has been specially designed to help learners gain a good command of Data Engineering : Google BigQuery &amp; Google Cloud, providing them with a solid foundation of knowledge to understand relevant professionals' job roles.</p><p>Through this Data Engineering : Google BigQuery &amp; Google Cloud course, you will gain a theoretical understanding of Data Engineering : Google BigQuery &amp; Google Cloud and others relevant subjects that will increase your employability in this field, help you stand out from the competition, and boost your earning potential in no time.</p><p>Not only that, but this Data Engineering : Google BigQuery &amp; Google Cloud training includes up-to-date knowledge and techniques that will ensure you have the most in-demand skills to rise to the top of the industry. </p><p>This course is fully CPD-accredited and broken down into several manageable modules, making it ideal for aspiring professionals.</p></div>
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										<span>Study at your convenient time and from wherever you want</span>
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										<span>Access to a computer or digital device with internet connectivity.</span>
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                                <h2>Course Curriculum</h2>
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					<td colspan="4"><strong>Unit 01: Introduction</strong></td>
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					<td>Module 01: Welcome to This Course</td><td><span>🕐 00:01:00</span></td>
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					<td>Module 02: How to Get Maximum Value from This Course</td><td><span>🕐 00:06:00</span></td>
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					<td>Module 03: Course Structure &amp; Coverage</td><td><span>🕐 00:02:00</span></td>
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					<td>Module 04: Technology in This Course</td><td><span>🕐 00:02:00</span></td>
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					<td>Module 01: Data Warehouse</td><td><span>🕐 00:07:00</span></td>
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					<td>Module 02: Start With BigQuery</td><td><span>🕐 00:05:00</span></td>
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					<td>Module 03: BigQuery Web User Interface</td><td><span>🕐 00:04:00</span></td>
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					<td colspan="4"><strong>Unit 02: Introducing Data Warehouse &amp; BigQuery</strong></td>
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					<td>Module 01: First Data</td><td><span>🕐 00:04:00</span></td>
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					<td>Module 02: Basic Exploration</td><td><span>🕐 00:16:00</span></td>
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					<td>Module 03: Functions</td><td><span>🕐 00:14:00</span></td>
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					<td>Module 05: Different Query</td><td><span>🕐 00:01:00</span></td>
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					<td>Module 06: Exploring Common Data Types</td><td><span>🕐 00:25:00</span></td>
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					<td>Module 01: Data Quality</td><td><span>🕐 00:06:00</span></td>
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					<td>Module 05: Clean &amp; Transform With Dataprep</td><td><span>🕐 00:25:00</span></td>
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					<td>Module 06: Scheduled Query</td><td><span>🕐 00:04:00</span></td>
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					<td>Module 07: Analyze Data</td><td><span>🕐 00:05:00</span></td>
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					<td>Module 08: Data Visualization</td><td><span>🕐 00:06:00</span></td>
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					<td colspan="4"><strong>Unit 04: Data Flow BasicUnit 05: Diving into BigQuery</strong></td>
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					<td>Module 01: Essential BigQuery</td><td><span>🕐 00:15:00</span></td>
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					<td>Module 02: Load Data into BigQuery (Part 1) - The Basic</td><td><span>🕐 00:36:00</span></td>
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					<td>Module 03: Tip: Mock Data</td><td><span>🕐 00:01:00</span></td>
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					<td>Module 04: Load Data into BigQuery (Part 2) - Handling Errors</td><td><span>🕐 00:22:00</span></td>
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					<td>Module 05: Load Data into BigQuery (Part 3) - Efficient Load</td><td><span>🕐 00:14:00</span></td>
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					<td>Module 06: Load Data into BigQuery (Part 4) - From Your Data to BigQuery</td><td><span>🕐 00:23:00</span></td>
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					<td>Module 07: Load Data into BigQuery (Part 5) - In Microservice Architecture</td><td><span>🕐 00:20:00</span></td>
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					<td>Module 08: Tip: Message Broker Overview</td><td><span>🕐 00:08:00</span></td>
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					<td>Module 09: Load Data into BigQuery (Part 6) - Recurring Load</td><td><span>🕐 00:12:00</span></td>
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					<td colspan="4"><strong>Unit 06: Virtual Data using View</strong></td>
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					<td>Module 01: BigQuery View</td><td><span>🕐 00:06:00</span></td>
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					<td colspan="4"><strong>Unit 07: Data Visualization</strong></td>
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					<td>Module 01: What We Will Learn</td><td><span>🕐 00:01:00</span></td>
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					<td>Module 02: Google Sheets &amp; BigQuery</td><td><span>🕐 00:10:00</span></td>
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					<td>Module 03: Google Data Studio</td><td><span>🕐 00:13:00</span></td>
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					<td colspan="4"><strong>Unit 08: Intermediate Query</strong></td>
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					<td>Module 01: Using Join - Theory</td><td><span>🕐 00:04:00</span></td>
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					<td>Module 02: Using Join - Hands On</td><td><span>🕐 00:16:00</span></td>
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					<td>Module 03: Union &amp; Intersect</td><td><span>🕐 00:06:00</span></td>
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					<td>Module 04: Basic Statistical Functions</td><td><span>🕐 00:05:00</span></td>
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				</tbody></table></div>

			</div>
		                        </div>

Computing Skills

Digital Skills

Gain the solid skills and knowledge to kickstart a successful career and learn from the experts with this

Data Engineering : Google BigQuery & Google Cloud

<p><strong>Develop in-demand skills for a better future with a super-saver bundle just </strong><strong>£129</strong><strong> and instantly save </strong><strong>£1570</strong><strong>!</strong></p><p><strong>This bundle includes 1 best selling course endorsed by the Quality Licence Scheme with 4 additional CPD-accredited courses, expert assistance and course assessment. Enjoy 12 months of access to this bundle of courses FREE of charge and master a range of in-demand professional skills to advance your career. No hidden costs - simply enrol this Data Engineering with Google BigQuery &amp; Google Cloud bundle.</strong></p><p>This Course package includes:</p><ul><li>Data Engineering with Google BigQuery &amp; Google Cloud with endorsed certificate</li><li>4 additional CPD accredited courses -<br /><ol><li>Linux for Cloud and DevOps Engineers</li><li>SQL NoSQL Big Data and Hadoop</li><li>Linux Shell Scripting</li><li>Linux Security and Hardening</li></ol></li></ul><p>Dedicated tutor support and 24/7 customer support are available to all students with this premium quality bundle. Get the help you require and the answers to all your queries throughout the comprehensive syllabus of this Data Engineering with Google BigQuery &amp; Google Cloud bundle.</p><p>This premium online course ensures your professional development with endorsement from Quality Licence Scheme and also CPD accreditation. You'll have the privilege of learning in your own time, at your own pace and earning an accredited certification.</p><p>With this bundle program, success becomes a lot easier that enables you to monetise your skills. This Data Engineering with Google BigQuery &amp; Google Cloud bundle is designed for both part-time and full-time students and can be completed at a pace that suits your learning style.</p><p><strong>Why People Enrol this Bundle from One Education:</strong></p><ul><li>Receive a Quality Licence Scheme-endorsed certificate upon successful completion of the bundle</li><li>4 additional CPD accredited courses to enrich your knowledge and skills</li><li>Learning materials of our Course contains engaging voiceover and visual elements for your comfort</li><li>Get 24/7 access to all bundle content for a full year</li><li>Complete the Course at your own pace</li><li>Each of our students gets full tutor support on weekdays (Monday to Friday)</li><li>Efficient assessments and instant results upon completion of our Course</li></ul><p><strong>Course Curriculum:</strong></p><p>Here is a curriculum breakdown of the course:</p><ul><li>Unit 01: Introduction</li><li>Unit 02: Introducing Data Warehouse &amp; BigQuery</li><li>Unit 03: First Exploration</li><li>Unit 04: Data Flow Basic</li><li>Unit 05: Diving into BigQuery</li><li>Unit 06: Virtual Data using View</li><li>Unit 07: Data Visualization</li><li>Unit 08: Intermediate Query</li></ul><p><strong>How is the Course assessed?</strong></p><p>To simplify the procedure of evaluation and accreditation for learners, we provide an automated assessment system. Upon completion of an online module, you will immediately be given access to a specifically crafted MCQ test. The results will be evaluated instantly, and the score displayed for your perusal. For each test, the pass mark will be set to 60%.</p><p>When all tests have been successfully passed, you will be able to claim a certificate endorsed by the Quality Licence Scheme.</p><p><strong>Certificate of Achievement</strong></p><p><strong>Endorsed Certificate of Achievement from the Quality Licence Scheme</strong></p><p>After successfully completing the Course, learners will get an endorsed certificate (included with the course) delivered right at their doorstep by post, without paying a single penny! Note that learners residing outside the UK have to pay a £10 postage charge.</p><p><strong>For Additional Courses</strong></p><p>For the additional Quality Licence Scheme endorsed certificates from the additional courses, you have to pay the fees based on level of each course:</p><ul><li>No Level- £29</li><li>Level 1 - £29</li><li>Level 2 - £59</li><li>Level 3 - £69</li><li>Level 4 - £79</li><li>Level 5 - £99</li><li>Level 6 - £109</li><li>Level 7 - £119</li></ul><p><strong>CPD Accredited Certification from One Education</strong></p><p>After successfully completing the courses under this Course, you will also qualify for CPD Accredited Certificates for each of the courses. Certification is available in PDF format, at the cost of £9, or a hard copy can be sent to you via post at £15.</p><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>The bundle training is ideal for highly motivated individuals who want to enhance their professional skills and train for the job they want! This Course also suits people aspiring for some in-depth knowledge on this topic and keep up to date with the latest information.</p><p>Study the Data Engineering with Google BigQuery &amp; Google Cloud bundle today and increase your professional skillset from the comfort of your home!</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>There are no formal entry requirements for the Course, with enrollment open to anyone!<strong> Anyone and everyone</strong> with a knack for learning can enrol on this course without any hesitation.</p><p>Learn online from any internet device, including your computer, tablet or smartphone. Study when it suits you and complete the Data Engineering with Google BigQuery &amp; Google Cloud bundle at your own pace.</p><p>All students must have a passion for learning and literacy, as well as being over the age of 16.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Studying the Course is designed to help you get the job of your dreams, or even that promotion you've always wanted. Learn the essential skills and knowledge you need to exceed in your professional life with the help &amp; guidance from our Course.</p>
                        </div>

One Education

Data Engineering with Google BigQuery & Google Cloud Course

<p><strong>Level 6 Diploma in Data Engineering with Google BigQuery &amp; Google Cloud</strong></p><p>Turn your skills into a competitive advantage that is recognised globally and endorsed for quality by QLS, the UK's most reputable high-quality course auditor.</p><p>Hone your skills in data analytics, big data, machine learning, data pipelines, and artificial intelligence! Create infrastructure for collecting, managing, and transforming raw data into interpretable information by data scientists and business analysts. Develop your ability to create data processing solutions, make data accessible, and evaluate and optimise organisational performance. Enrol to advance your Cloud career and show your proficiency in one of the most sought-after industries in the market.</p><p>This premium QLS endorsed Data Engineering with Google BigQuery &amp; Google Cloud course comes with intensive study modules, dedicated tutor assistance, customer support, flexible learning opportunity and a globally recognised certification all-together. Thus, successful completion of our Data Engineering with Google BigQuery &amp; Google Cloud course will give you limitless opportunities anywhere and everywhere, since the value of QLS endorsed courses are quite high, to say the least!!</p><p>What's more, the quality of our first-class course is uncompromising for both you and us. You will be taught the richest of materials from this exquisite Data Engineering with Google BigQuery &amp; Google Cloud course, enabling you to open up a vast world of opportunities for you to grasp and gain success from. For the price point, this course is actually an absolute steal! It's an investment you absolutely do not want to miss out on!</p><p>So, why delay any longer? Benefit your career progression by joining us today and distinguish yourself as, unquestionably, the most skilled one in your workplace!</p><p><strong>Learning Outcomes for Level 6 Diploma in Data Engineering with Google BigQuery &amp; Google Cloud:</strong></p><ol><li>Develop a comprehensive understanding of data engineering principles and concepts.</li><li>Utilise Google BigQuery and Google Cloud for efficient data warehousing and analysis.</li><li>Explore and manipulate data effectively using BigQuery for insightful data-driven decisions.</li><li>Apply data flow techniques to design and optimise data pipelines.</li><li>Implement virtual data solutions using views for efficient data organisation and retrieval.</li><li>Create visually appealing and informative data visualisations to communicate insights effectively.</li></ol><p><strong>Why Learn with us: </strong></p><p>We, as one of the leading e-learning service providers across the globe, strive to provide all our learners with the best e-learning experience possible that can make a real difference in their career progression.</p><p><strong>Our Service for the </strong><strong>Data Engineering with Google BigQuery &amp; Google Cloud</strong><strong> Includes:</strong></p><ul><li>Intensive Study Notes</li><li>Tutor Support</li><li>Customer Support</li><li>Assignment Help</li><li>QLS Endorsed Certificate</li><li>24/7 Learning Portal Access</li><li>Widely Compatible Study Materials</li></ul><p><strong>Course Curriculum of </strong><strong>Data Engineering with Google BigQuery &amp; Google Cloud</strong></p><ul><li><strong>Unit 01: </strong>Introduction<strong><br /></strong></li><li><strong>Unit 02: </strong>Introducing Data Warehouse &amp; BigQuery<strong><br /></strong></li><li><strong>Unit 03: </strong>First Exploration<strong><br /></strong></li><li><strong>Unit 04: </strong>Data Flow Basic<strong><br /></strong></li><li><strong>Unit 05: </strong>Diving into BigQuery<strong><br /></strong></li><li><strong>Unit 06: </strong>Virtual Data using View<strong><br /></strong></li><li><strong>Unit 07: </strong>Data Visualisation<strong><br /></strong></li><li><strong>Unit 08: </strong>Intermediate Query</li></ul><p><strong>Assessment &amp; Certification</strong></p><p>Learners must submit a comprehensive summerised assignment on all the units that will be assessed by our expert tutor if all the learning outcomes are met as per the standard set by QLS. After the quality check, learner will be provided with the Data Engineering with Google BigQuery &amp; Google Cloud certificate.</p><p><strong>Endorsed Certificate of Achievement from the Quality Licence Scheme.</strong></p><p>An endorsed certificate will be issued to learners at the end of the course as recognition of course completion. Provided that learner completes all the assessment of a course can claim for certificate.</p><p><strong>Endorsement:</strong></p><p>QLS endorsed this certified course as a highly qualified, non-regulated provision and training programme. There will be a trainer to answer all your questions including your progression routes into further higher education.</p><h2>
        
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                                        10 CPD hours / points
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                                            Accredited by CPD Quality Standards
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        <div>Who is this course for?</div>
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                            <p>Our course is open for everyone. This Data Engineering with Google BigQuery &amp; Google Cloud is ideal for those who aspire to gain in-depth knowledge &amp; efficient skill to embark into the relevant sector as a promising potential.</p>
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        <div>Requirements</div>
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                            <p>There are no formal requirements needed for this Data Engineering with Google BigQuery &amp; Google Cloud course. So learners do not require any prior qualifications to enrol in this course.</p>
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        <div>Career path</div>
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                            <p><strong>Here are few job roles related to Data Engineering with Google BigQuery &amp; Google Cloud </strong>(Salary-per annum):</p><ol><li>Data Engineer (£50,000 - £55,000)</li><li>Data Analyst: (£38,000 - £40,000)</li><li>Data Scientist (£40,000 - £70,000)</li><li>Data Architect (£80,000 - £90,000)</li><li>Cloud Data Engineer (£50,000 - £80,000)</li><li>Big Data Engineer (£50,000 - £80,000)</li></ol>
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Kingston Open College

Learning & Development

ELS (Effective Learning Service)

ICDL (International Certification of Digital Literacy)

QLS Endorsed + CPD QS Accredited - Dual Certification | Instant Access | 24/7 Tutor Support | All-Inclusive Cost

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