1 Data Processing courses in London

Duration 5 Days 30 CPD hours Overview Mining data Manipulating data Visualizing and reporting data Applying basic statistical methods Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. CompTIA Data+ gives you the confidence to bring data analysis to life. As the importance for data analytics grows, more job roles are required to set context and better communicate vital business intelligence. Collecting, analyzing, and reporting on data can drive priorities and lead business decision-making. 1 - IDENTIFYING BASIC CONCEPTS OF DATA SCHEMAS * Identify Relational and Non-Relational Databases * Understand the Way We Use Tables, Primary Keys, and Normalization 2 - UNDERSTANDING DIFFERENT DATA SYSTEMS * Describe Types of Data Processing and Storage Systems * Explain How Data Changes 3 - UNDERSTANDING TYPES AND CHARACTERISTICS OF DATA * Understand Types of Data * Break Down the Field Data Types 4 - COMPARING AND CONTRASTING DIFFERENT DATA STRUCTURES, FORMATS, AND MARKUP LANGUAGES * Differentiate between Structured Data and Unstructured Data * Recognize Different File Formats * Understand the Different Code Languages Used for Data 5 - EXPLAINING DATA INTEGRATION AND COLLECTION METHODS * Understand the Processes of Extracting, Transforming, and Loading Data * Explain API/Web Scraping and Other Collection Methods * Collect and Use Public and Publicly-Available Data * Use and Collect Survey Data 6 - IDENTIFYING COMMON REASONS FOR CLEANSING AND PROFILING DATA * Learn to Profile Data * Address Redundant, Duplicated, and Unnecessary Data * Work with Missing Value * Address Invalid Data * Convert Data to Meet Specifications 7 - EXECUTING DIFFERENT DATA MANIPULATION TECHNIQUES * Manipulate Field Data and Create Variables * Transpose and Append Data * Query Data 8 - EXPLAINING COMMON TECHNIQUES FOR DATA MANIPULATION AND OPTIMIZATION * Use Functions to Manipulate Data * Use Common Techniques for Query Optimization 9 - APPLYING DESCRIPTIVE STATISTICAL METHODS * Use Measures of Central Tendency * Use Measures of Dispersion * Use Frequency and Percentages 10 - DESCRIBING KEY ANALYSIS TECHNIQUES * Get Started with Analysis * Recognize Types of Analysis 11 - UNDERSTANDING THE USE OF DIFFERENT STATISTICAL METHODS * Understand the Importance of Statistical Tests * Break Down the Hypothesis Test * Understand Tests and Methods to Determine Relationships Between Variables 12 - USING THE APPROPRIATE TYPE OF VISUALIZATION * Use Basic Visuals * Build Advanced Visuals * Build Maps with Geographical Data * Use Visuals to Tell a Story 13 - EXPRESSING BUSINESS REQUIREMENTS IN A REPORT FORMAT * Consider Audience Needs When Developing a Report * Describe Data Source Considerations For Reporting * Describe Considerations for Delivering Reports and Dashboards * Develop Reports or Dashboards * Understand Ways to Sort and Filter Data 14 - DESIGNING COMPONENTS FOR REPORTS AND DASHBOARDS * Design Elements for Reports and Dashboards * Utilize Standard Elements * Creating a Narrative and Other Written Elements * Understand Deployment Considerations 15 - UNDERSTAND DEPLOYMENT CONSIDERATIONS * Understand How Updates and Timing Affect Reporting * Differentiate Between Types of Reports 16 - SUMMARIZING THE IMPORTANCE OF DATA GOVERNANCE * Define Data Governance * Understand Access Requirements and Policies * Understand Security Requirements * Understand Entity Relationship Requirements 17 - APPLYING QUALITY CONTROL TO DATA * Describe Characteristics, Rules, and Metrics of Data Quality * Identify Reasons to Quality Check Data and Methods of Data Validation 18 - EXPLAINING MASTER DATA MANAGEMENT CONCEPTS * Explain the Basics of Master Data Management * Describe Master Data Management Processes ADDITIONAL COURSE DETAILS: Nexus Humans CompTIA Data Plus (DA0-001) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. 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. While we feel this is the best course for the CompTIA Data Plus (DA0-001) 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. 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.

Duration 1 Days 6 CPD hours This course is intended for The audience for this course is individuals who want to learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure. Overview Describe core data concepts Identify considerations for relational data on Azure Describe considerations for working with non-relational data on Azure Describe an analytics workload on Azure In this course, students will gain foundational knowledge of core data concepts and related Microsoft Azure data services. Students will learn about core data concepts such as relational, non-relational, big data, and analytics, and build their foundational knowledge of cloud data services within Microsoft Azure. Students will explore fundamental relational data concepts and relational database services in Azure. They will explore Azure storage for non-relational data and the fundamentals of Azure Cosmos DB. Students will learn about large-scale data warehousing, real-time analytics, and data visualization. 1 - EXPLORE CORE DATA CONCEPTS * Identify data formats * Explore file storage * Explore databases * Explore transactional data processing * Explore analytical data processing 2 - EXPLORE DATA ROLES AND SERVICES * Explore job roles in the world of data * Identify data services 3 - EXPLORE FUNDAMENTAL RELATIONAL DATA CONCEPTS * Understand relational data * Understand normalization * Explore SQL * Describe database objects 4 - EXPLORE RELATIONAL DATABASE SERVICES IN AZURE * Describe Azure SQL services and capabilities * Describe Azure services for open-source databases 5 - EXPLORE AZURE STORAGE FOR NON-RELATIONAL DATA * Explore Azure blob storage * Explore Azure DataLake Storage Gen2 * Explore Azure Files * Explore Azure Tables 6 - EXPLORE FUNDAMENTALS OF AZURE COSMOS DB * Describe Azure Cosmos DB * Identify Azure Cosmos DB APIs 7 - EXPLORE FUNDAMENTALS OF LARGE-SCALE DATA WAREHOUSING * Describe data warehousing architecture * Explore data ingestion pipelines * Explore analytical data stores 8 - EXPLORE FUNDAMENTALS OF REAL-TIME ANALYTICS * Understand batch and stream processing * Explore common elements of stream processing architecture * Explore Azure Stream Analytics * Explore Apache Spark on Microsoft Azure 9 - EXPLORE FUNDAMENTALS OF DATA VISUALIZATION * Describe Power BI tools and workflow * Describe core concepts of data modeling * Describe considerations for data visualization

Duration 2 Days 12 CPD hours This course is intended for Experienced DataStage developers seeking training in more advanced DataStage job techniques and who seek techniques for working with complex types of data resources. Overview Use Connector stages to read from and write to database tables Handle SQL errors in Connector stages Use Connector stages with multiple input links Use the File Connector stage to access Hadoop HDFS data Optimize jobs that write to database tables Use the Unstructured Data stage to extract data from Excel spreadsheets Use the Data Masking stage to mask sensitive data processed within a DataStage job Use the Hierarchical stage to parse, compose, and transform XML data Use the Schema Library Manager to import and manage XML schemas Use the Data Rules stage to validate fields of data within a DataStage job Create custom data rules for validating data Design a job that processes a star schema data warehouse with Type 1 and Type 2 slowly changing dimensions This course is designed to introduce you to advanced parallel job data processing techniques in DataStage v11.5. In this course you will develop data techniques for processing different types of complex data resources including relational data, unstructured data (Excel spreadsheets), and XML data. In addition, you will learn advanced techniques for processing data, including techniques for masking data and techniques for validating data using data rules. Finally, you will learn techniques for updating data in a star schema data warehouse using the DataStage SCD (Slowly Changing Dimensions) stage. Even if you are not working with all of these specific types of data, you will benefit from this course by learning advanced DataStage job design techniques, techniques that go beyond those utilized in the DataStage Essentials course. ACCESSING DATABASES * Connector stage overview * - Use Connector stages to read from and write to relational tables * - Working with the Connector stage properties * Connector stage functionality * - Before / After SQL * - Sparse lookups * - Optimize insert/update performance * Error handling in Connector stages * - Reject links * - Reject conditions * Multiple input links * - Designing jobs using Connector stages with multiple input links * - Ordering records across multiple input links * File Connector stage * - Read and write data to Hadoop file systems * Demonstration 1: Handling database errors * Demonstration 2: Parallel jobs with multiple Connector input links * Demonstration 3: Using the File Connector stage to read and write HDFS files PROCESSING UNSTRUCTURED DATA * Using the Unstructured Data stage in DataStage jobs * - Extract data from an Excel spreadsheet * - Specify a data range for data extraction in an Unstructured Data stage * - Specify document properties for data extraction. * Demonstration 1: Processing unstructured data DATA MASKING * Using the Data Masking stage in DataStage jobs * - Data masking techniques * - Data masking policies * - Applying policies for masquerading context-aware data types * - Applying policies for masquerading generic data types * - Repeatable replacement * - Using reference tables * - Creating custom reference tables * Demonstration 1: Data masking USING DATA RULES * Introduction to data rules * - Using the Data Rules Editor * - Selecting data rules * - Binding data rule variables * - Output link constraints * - Adding statistics and attributes to the output information * Use the Data Rules stage to valid foreign key references in source data * Create custom data rules * Demonstration 1: Using data rules PROCESSING XML DATA * Introduction to the Hierarchical stage * - Hierarchical stage Assembly editor * - Use the Schema Library Manager to import and manage XML schemas * Composing XML data * - Using the HJoin step to create parent-child relationships between input lists * - Using the Composer step * Writing Hierarchical data to a relational table * Using the Regroup step * Consuming XML data * - Using the XML Parser step * - Propagating columns * Topic 6: Transforming XML data * - Using the Aggregate step * - Using the Sort step * - Using the Switch step * - Using the H-Pivot step * Demonstration 1: Importing XML schemas * Demonstration 2: Compose hierarchical data * Demonstration 3: Consume hierarchical data * Demonstration 4: Transform hierarchical data UPDATING A STAR SCHEMA DATABASE * Surrogate keys * - Design a job that creates and updates a surrogate key source key file from a dimension table * Slowly Changing Dimensions (SCD) stage * - Star schema databases * - SCD stage Fast Path pages * - Specifying purpose codes * - Dimension update specification * - Design a job that processes a star schema database with Type 1 and Type 2 slowly changing dimensions * Demonstration 1: Build a parallel job that updates a star schema database with two dimensions ADDITIONAL COURSE DETAILS: Nexus Humans KM423 IBM InfoSphere DataStage v11.5 - Advanced Data Processing training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. 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. While we feel this is the best course for the KM423 IBM InfoSphere DataStage v11.5 - Advanced Data Processing 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. 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.

Duration 4 Days 24 CPD hours This course is intended for While no prior programming or web development experience is required, target students should have good foundational computer skills. Overview Set up the tools and resources you need to perform Web Development. Create web pages in HTML, constructing valid, well-formed elements, including navigation links, sections, titles, and semantic markup. Enhance HTML content with tables, images, movies, and audio. Apply styles to HTML elements using CSS. Use CSS to format the edges, size, position, and layering of HTML elements. Apply complex style rules using advanced CSS selectors, including pseudo-class selectors, structural selectors, and pseudo-element selectors. Create complex layouts using CSS newspaper style columns, grid layouts, and flexible box layouts. Improve the quality of web content, including adaptability (different displays and devices), searchability, usability, and accessibility. Submit data through URL query strings and web forms for processing by a web application server. Write JavaScript code to make web pages more interactive, perform data processing tasks directly in the browser, and manipulate items in the current web page. Write JavaScript code to iterate through collections of elements in a page to get and set their attributes and add event listener code. Use third-party libraries and frameworks for web front-end development. Modern organizations depend heavily on the web to perform core business operations such as marketing, advertising, and selling products, providing services, and communicating with customers, partner organizations, and employees. Whatever you're creating on the web, HTML, CSS, and JavaScript? likely play an important role. These three languages provide the core toolkit for anyone looking to perform web development work. This course covers the fundamentals of web development using these three languages. Prerequisites This course assumes that students have strong experience working with computers. Previous experience programming in other languages is helpful, but not required for students to benefit from this course. LESSON 1: SETTING UP YOUR WEB DEVELOPMENT ENVIRONMENT * Topic A: Prepare Your Web Platform * Topic B: Prepare Your Web Development Tools and Processes * Topic C: Monitor the Web Request-Response Cycle LESSON 2: CREATING WEB CONTENT IN HTML * Topic A: Create a Basic Web Page * Topic B: Provide Navigation Links Between Web Pages * Topic C: Improve Web Page Structure and Navigation LESSON 3: ADDING TABLES AND MULTIMEDIA CONTENT TO A WEB PAGE * Topic A: Create a Table * Topic B: Embed Images, Movies, and Audio in a Web Page LESSON 4: APPLYING STYLES TO WEB CONTENT * Topic A: Apply Styles to HTML * Topic B: Create a Style Sheet * Topic C: Use Web Fonts LESSON 5: CONTROLLING EDGES, SIZE, AND POSITION * Topic A: Format Element Edges and Corners * Topic B: Control an Element's Height and Width * Topic C: Control an Element's Position and Layering * Topic D: Normalize and Reset Browser CSS Defaults LESSON 6: APPLYING COMPLEX STYLE RULES * Topic A: Use Advanced Selectors * Topic B: Manage User Interface States * Topic C: Make Structure Apparent to Users * Topic D: Use CSS Pseudo-Element Selectors LESSON 7: CREATING COMPLEX LAYOUTS * Topic A: Use CSS to Create Newspaper Style Columns * Topic B: Use CSS to Create Grid Layouts * Topic C: Use CSS to Create Flexible Box Layouts LESSON 8: IMPROVING WEB CONTENT * Topic A: Adjust the Layout for a Wide Variety of Devices * Topic B: Perform Basic Search Engine Optimization * Topic C: Test Your Website LESSON 9: SUBMITTING DATA TO A WEB SERVER FOR PROCESSING * Topic A: Submit Data Through a URL * Topic B: Submit Data Through a Web Form LESSON 10: WRITING JAVASCRIPT CODE * Topic A: Add JavaScript to a Web Page * Topic B: Perform Operations on Data * Topic C: Program Repetitive Tasks * Topic D: Manipulate DOM Objects LESSON 11: ENUMERATING AND PROCESSING COLLECTIONS OF ELEMENTS * Topic A: Enumerate Elements * Topic B: Attach Events Through Code LESSON 12: USING THIRD-PARTY LIBRARIES AND FRAMEWORKS * Topic A: Use a Third-Party JavaScript Library * Topic B: Create a Web Page Based on a Third-Party Framework ADDITIONAL COURSE DETAILS: Nexus Humans Web Development with HTML5, CSS, and JavaScript (v1.0) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. 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. While we feel this is the best course for the Web Development with HTML5, CSS, and JavaScript (v1.0) 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. 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.

  The IAPP offers the most encompassing, up-to-date and sought-after global training and certification program for privacy and data protection. The Certified Information Privacy Professional (CIPP) helps organizations around the world bolster compliance and risk mitigation practices, and arms practitioners with the insight needed to add more value to their businesses. Skilled privacy pros are in high demand and IAPP certification is what employers want. When you earn an IAPP credential, you earn the right to be recognized as part of an elite group of knowledgeable, capable and dedicated privacy professionals. With the GDPR effective as of May 2018, among its mandates was the requirement to appoint knowledgeable DPOs (data protection officers) tasked with monitoring compliance, managing internal data protection activities, training data processing staff, conducting internal audits and more. There's a lot to know, there's a lot at stake and there's a lot of opportunity for privacy professionals with the right training and education. Achieving a CIPP/E credential shows you have the comprehensive GDPR knowledge, perspective and understanding to ensure compliance and data protection success in Europe-and to take advantage of the career opportunity this sweeping legislation represents. ABOUT THIS COURSE   Delivered in a Modular format, the course includes; * Module 1: Data Protection Laws Introduces key European data protection laws and regulatory bodies, describing the evolution toward a Harmonised European Legislative Framework. * Module 2: Personal Data Defines and differentiates between types of data-including personal, anonymous, pseudo-anonymous and special categories. * Module 3: Controllers and Processors Describes the roles and relationships of controllers and processors. * Module 4: Processing Personal Data Defines data processing and GDPR processing principles, Explains the application of the GDPR and outlines the legitimate bases for processing personal data. * Module 5: Information provision Explains controller obligations for providing information about data processing activities to data subjects and Supervisory Authorities. * Module 6: Data Subjects 'Rights Describes data subjects' rights, applications of rights and obligations controller and processor. * Module 7: Security or Processing Discusses considerations and duties of controllers and processors for Ensuring security of personal data and providing notification of data breaches. * Module 8: Accountability Investigates accountability requirements, data protection management systems, data protection impact assessments, privacy policies and the role of the data protection officer. * Module 9: International Data Transfers Outlines options and obligations for transferring data outside the European Economic Area, Decisions adequacy and appropriateness safeguards and derogations. * Module 10: Supervision and Enforcement Describes the role, powers and procedures or Supervisory Authorities; the composition and tasks of the European Data Protection Board; the role of the European Data Protection Supervisor; and remedies, liabilities and penalties for non-compliance. * Module 11: Compliance Discusses the applications of European data protection law, legal bases and compliance requirements for processing personal data in practice, employers-including processing employee data, surveillance, direct marketing, Internet technology and communications and outsourcing. PREREQUISITES   There are no prerequisites for this course but candidates would benefit from reading the freely available materials found on the IAPP website. WHAT'S INCLUDED?   1 years membership of the IAPP  Breakfast, Lunch and refreshments (Classroom courses only) Official Study Guide (European Data Protection, Law & Practice)* Participant Guide* Official Exam Q&A* Official Practice Exam Official Practice Exam* The Exam Fees * In electronic format for Live Online and hard copy for Classroom delegates     WHO SHOULD ATTEND?   The CIPP/E is ideal for IT and information security leaders responsible for applying best practices to cloud security architecture, design, operations and service orchestration, including those in the following positions: Cybersecurity Analysts Data Analysts Security Administrators Aspiring Data Protection Officers ACCREDITATION OUR GUARANTEE   * We are an approved IAPP Training Partner. * You can learn wherever and whenever you want with our robust classroom and interactive online training courses. * Our courses are taught by qualified practitioners with a minimum of 25 years commercial experience. * We strive to give our delegates the hands-on experience. * Our courses are all-inclusive with no hidden extras.  The one-off cost covers the training, all course materials, and exam voucher. * Our aim: To achieve a 100% first time pass rate on all our instructor-led courses. * Our Promise: Pass first time or 'train' again for FREE. *FREE training offered for retakes - come back within a year and only pay for the exam.

Duration 1 Days 6 CPD hours This course is intended for 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. Job role: Data Analyst, Data Engineer, Data Scientist Overview Describe end-to-end analytics in Microsoft Fabric Describe core features and capabilities of lakehouses in Microsoft Fabric Create a lakehouse Ingest data into files and tables in a lakehouse Query lakehouse tables with SQL Configure Spark in a Microsoft Fabric workspace Identify suitable scenarios for Spark notebooks and Spark jobs Use Spark dataframes to analyze and transform data Use Spark SQL to query data in tables and views Visualize data in a Spark notebook Understand Delta Lake and delta tables in Microsoft Fabric Create and manage delta tables using Spark Use Spark to query and transform data in delta tables Use delta tables with Spark structured streaming Describe Dataflow (Gen2) capabilities in Microsoft Fabric Create Dataflow (Gen2) solutions to ingest and transform data Include a Dataflow (Gen2) in a pipeline 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. INTRODUCTION TO END-TO-END ANALYTICS USING MICROSOFT FABRIC * Explore end-to-end analytics with Microsoft Fabric * Data teams and Microsoft Fabric * Enable and use Microsoft Fabric * Knowledge Check GET STARTED WITH LAKEHOUSES IN MICROSOFT FABRIC * Explore the Microsoft Fabric Lakehouse * Work with Microsoft Fabric Lakehouses * Exercise - Create and ingest data with a Microsoft Fabric Lakehouse USE APACHE SPARK IN MICROSOFT FABRIC * Prepare to use Apache Spark * Run Spark code * Work with data in a Spark dataframe * Work with data using Spark SQL * Visualize data in a Spark notebook * Exercise - Analyze data with Apache Spark WORK WITH DELTA LAKE TABLES IN MICROSOFT FABRIC * Understand Delta Lake * Create delta tables * Work with delta tables in Spark * Use delta tables with streaming data * Exercise - Use delta tables in Apache Spark INGEST DATA WITH DATAFLOWS GEN2 IN MICROSOFT FABRIC * Understand Dataflows (Gen2) in Microsoft Fabric * Explore Dataflows (Gen2) in Microsoft Fabric * Integrate Dataflows (Gen2) and Pipelines in Microsoft Fabric * Exercise - Create and use a Dataflow (Gen2) in Microsoft Fabric

  European Data Protection   Principles of Data Protection in Europe covers the essential pan-European and national data protection laws, as well as industry-standard best practices for corporate compliance with these laws. Those taking this course will gain an understanding of the European model for privacy enforcement, key privacy terminology and practical concepts concerning the protection of personal data and trans-border data flows.   The training is based on the body of knowledge for the IAPP's ANSI-accredited Certified Information Privacy Professional/Europe (CIPP/E) certification program. Privacy Programme Management   Principles of Privacy Management is the how-to training on implementing a privacy program framework, managing the privacy program operational lifecycle and structuring a knowledgeable, high-performing privacy team. Those taking this course will learn the skills to manage privacy in an organisation through process and technology-regardless of jurisdiction or industry.   The Principles of Privacy Program Management training is based on the body of knowledge for the IAPP's ANSI-accredited Certified Information Privacy Manager (CIPM) certification programme. Make a difference in your organization and in your career. The CIPM designation says that you're a leader in privacy program administration and that you've got the goods to establish, maintain and manage a privacy program across all stages of its lifecycle.  ABOUT THIS COURSE   Delivered in a modular format, this four day course covers   Days 1 & 2   * Module 1: Data Protection Laws Introduces key European data protection laws and regulatory bodies, describing the evolution toward a Harmonised European Legislative Framework.  * Module 2: Personal Data Defines and differentiates between types of data-including personal, anonymous, pseudo-anonymous and special categories.  * Module 3: Controllers and Processors Describes the roles and relationships of controllers and processors.  * Module 4: Processing Personal Data Defines data processing and GDPR processing principles, Explains the application of the GDPR and outlines the legitimate bases for processing personal data. *  Module 5: Information provision Explains controller obligations for providing information about data processing activities to data subjects and Supervisory Authorities.  * Module 6: Data Subjects 'Rights Describes data subjects' rights, applications of rights and obligations controller and processor.  * Module 7: Security or Processing Discusses considerations and duties of controllers and processors for Ensuring security of personal data and providing notification of data breaches.  * Module 8: Accountability Investigates accountability requirements, data protection management systems, data protection impact assessments, privacy policies and the role of the data protection officer.  * Module 9: International Data Transfers Outlines options and obligations for transferring data outside the European Economic Area, Decisions adequacy and appropriateness safeguards and derogations.  * Module 10: Supervision and Enforcement Describes the role, powers and procedures or Supervisory Authorities; the composition and tasks of the European Data Protection Board; the role of the European Data Protection Supervisor; and remedies, liabilities and penalties for non-compliance.  * Module 11: Compliance Discusses the applications of European data protection law, legal bases and compliance requirements for processing personal data in practice, employers-including processing employee data, surveillance, direct marketing, Internet technology and communications and outsourcing.    Days 3 & 4   * Module 1: Introduction to privacy program management Identifies privacy program management responsibilities, and describes the role of accountability in privacy program management.  * Module 2: Privacy governance Examines considerations for developing and implementing a privacy program, including the position of the privacy function within the organization, role of the DPO, program scope and charter, privacy strategy, support and ongoing involvement of key functions and privacy frameworks.  * Module 3: Applicable laws and regulations Discusses the regulatory environment, common elements across jurisdictions and strategies for aligning compliance with organizational strategy.  * Module 4: Data assessments Relates practical processes for creating and using data inventories/maps, gap analyses, privacy assessments, privacy impact assessments/data protection impact assessments and vendor assessments.  * Module 5: Policies Describes common types of privacy-related policies, outlines components and offers strategies for implementation.  * Module 6: Data subject rights Discusses operational considerations for communicating and ensuring data subject rights, including privacy notice, choice and consent, access and rectification, data portability, and erasure and the right to be forgotten.  * Module 7: Training and awareness Outlines strategies for developing and implementing privacy training and awareness programs.  * Module 8: Protecting personal information Examines a holistic approach to protecting personal information through privacy by design.  * Module 9: Data breach incident plans Provides guidance on planning for and responding to a data security incident or breach.  * Module 10: Measuring, monitoring and auditing program performance Relates common practices for monitoring, measuring, analyzing and auditing privacy program performance PREREQUISITES   There are no prerequisites for this course but attendees would benefit from a review of the materials on the IAPP SITE [https://iapp.org/] WHAT'S INCLUDED?   1 years membership of the IAPP Breakfast, Lunch, mid-morning and afternoon snacks, teas, coffees Official Study Guides* Official Participant Guides* Official Exam Q&A's* Both exam fees * In electronic format for Live Online and hard copy for Classroom delegates     WHO SHOULD ATTEND?   This course is suitable for aspiring Data Protection Officers, as well as Information Security Managers, Lawyers, Data Managers, Analysts and Risk Teams. PROVIDED BY OUR GUARANTEE   * We are an approved IAPP Training Partner. * You can learn wherever and whenever you want with our robust classroom and interactive online training courses. * Our courses are taught by qualified practitioners with a minimum of 25 years commercial experience. * We strive to give our delegates the hands-on experience. * Our courses are all-inclusive with no hidden extras.  The one-off cost covers the training, all course materials, and exam voucher. * Our aim: To achieve a 100% first time pass rate on all our instructor-led courses. * Our Promise: Pass first time or 'train' again for FREE. *FREE training offered for retakes - come back within a year and only pay for the exam.

In terms of data processing and analytics, Azure Synapse Analytics is a game-changer. This course will teach you all you need to know about Azure SQL Data Warehouse, Azure Synapse Analytics Service, PolyBase, Cloud Data Warehouse, and Microsoft SQL Data Warehouse foundations.

Delve into big data streaming with Azure using Event Hubs, Data Lake, and Azure Stream Analytics