Description

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.

This course is ideal for those with a grasp of data concepts and cloud computing basics, especially in Microsoft Azure. Programming skills in SQL, Spark, and Python are beneficial but not mandatory. You'll begin with an introduction to Microsoft Fabric, delving into its objectives and success criteria, and explore the contrasting architectures of Lakehouse and Warehouse, along with insights into licensing, workspace creation, and configuration. Progress to mastering OneLake and Delta Lake, ensuring data security with authentication and authorization, while tackling Spark's complexities, data hub management, and warehouse management. This includes everything from understanding datasets and ingestion methods to utilizing Spark for real-time data processing, exploring SQL and KQL differences, and experiencing data flow architecture and Power BI visualizations in the Data Factory. The course concludes with a deep dive into Data Science and robust Data Management, ensuring you are equipped with the knowledge to control access, govern data, and monitor your systems effectively in any professional setting.

What You Will Learn

Discover the principles of data engineering in Microsoft Fabric, including Lakehouse and Delta Lake
Construct and manage data warehouses with Fabric's tools
Perform real-time analytics using SQL, KQL, and Spark
Build and execute data pipelines in the Data Factory module
Create compelling data stories through Power BI visualizations
Explore how to manage access control, governance, and monitoring in the Fabric environment

Audience

This course is perfect for citizen data practitioners and professionals in data infrastructure, offering insights into utilizing Microsoft Fabric for efficient workflows. Business analysts eager to enhance their expertise will find valuable lessons in data engineering practices, data lakes, and leveraging Power BI for dynamic reporting and visualization. Data scientists looking to integrate Fabric into their projects will explore model management and Azure services to elevate their analytical prowess.

Approach

The course adopts a hands-on, interactive approach, beginning with foundational Fabric principles and progressing through practical applications and real-world scenarios. Learners engage with the material through a mix of theoretical exploration and active problem-solving.

Key Features

From basics to advanced techniques across data engineering, warehousing, and science within the Microsoft Fabric ecosystem * Hands-on exercises and real-life case studies to apply what you've learned directly to your work * Equip yourself with the expertise required to lead in the data-driven world, with a focus on the latest tools and technologies

Github Repo

https://github.com/PacktPublishing/Microsoft-Fabric-Complete-Guide-The-Future-of-Data-with-Fabric

About the Author

HHN Automate Book Inc.

Henry Habib is a seasoned manager at a leading management consulting firm. He leverages his expertise to provide counsel on growth strategy, operation, and analytics to Fortune 500 companies. With a strong background in implementing data-driven solutions, Henry has a proven track record of making an impact in organizations of all sizes. He strongly advocates for no-code application development in business and deploys such solutions for his clients. These solutions are not only easier to understand but also quicker to implement. In addition to his consulting work, Henry is a dedicated professor who takes pleasure in guiding students toward success in various fields, ranging from case interviews to no-code application development and automation. His courses are designed to be engaging and informative, and he is always available to assist students in mastering challenging concepts.

Course Outline

1. Introduction

Learn about the course objectives, the instructors, and how to align analytical solutions with the needs of the clients.

1. Course Introduction

Get acquainted with the course's structure, goals, and the transformative skills you'll acquire.

2. Instructor's Introduction

Meet your instructors, Sawyer Nyquist a data professional from West Michigan, USA, holding the position of Sr. Data Engineering Consultant at Microsoft and Hitesh Govind, a cloud solutions architect from Southern California, USA, with a wide expertise in database administration and enterprise architecture.

3. Learning Objectives

The learning objective of the course is designed to enable data professionals to harness the power of Microsoft Fabric. It provides a thorough introduction, equipping you with the skills to craft and execute sophisticated analytics solutions that align with your strategic business goals for informed decision-making.

2. Microsoft Fabric

Explore the core of Microsoft Fabric, learning to align data engineering solutions with business goals and dive into practical steps for setting success metrics. Progress through an in-depth introduction, course navigation, and hands-on workspace configuration to fully grasp Fabric's capabilities and licensing options.

1. Understanding the Objectives

This video guides data engineering professionals on aligning IT solutions with business objectives, emphasizing the creation of meaningful and purpose-driven designs. It outlines a strategic methodology within Microsoft Fabric to drive value and optimize decision-making through stakeholder collaboration, data sourcing, and efficient architecture.

2. Success Criteria

This video emphasizes the importance of clear objectives and measurable outcomes in designing effective analytics solutions with Microsoft Fabric. It outlines steps to define success criteria, including aligning with business goals, setting measurable KPIs, establishing tracking methods, and periodic evaluations for optimizing data-driven solutions.

3. Introduction to Fabric

Receive an insightful introduction to the functionalities and benefits of Microsoft Fabric.

4. Course Roadmap

Discover the roadmap of our course, starting with an introduction and progressing through setting up the environment, understanding Microsoft Fabric's core concepts, and exploring data engineering, warehousing, integration, science, visualization, management, governance, and security to build a total solution.

5. Overview of Microsoft Fabric

Gain a broad understanding of Microsoft Fabric and its place in the data ecosystem.

6. Comparison of Lakehouse and Warehouse

Explore the distinctive features and advantages of Lakehouse compared to traditional Warehouses.

7. Fabric License Types

Learn about the different Fabric license types mainly PPU and Capacity, and which is best suited for your needs.

8. Signing-up to Fabric

Walk through the process of signing up and getting started with Fabric.

9. Workspaces Concept

Delve into the concept of workspaces and their role in Microsoft Fabric

10. Workspace Access Creation and Configuration

Step by step, learn how to create and configure access to Fabric workspaces.

11. Workspace Settings

Customize your workspace settings to optimize your Fabric environment.

3. Data Engineering

Delve into the essentials of Data Engineering in Microsoft Fabric with a focus on key components like OneLake, Lakehouse, and Delta Lake, and learn how to leverage these in data management. Discover the practicalities of data security, the creation and use of shortcuts, and gain expertise in using Spark and notebooks for efficient data processing and job monitoring within the Fabric ecosystem.

1. Introduction to Data Engineering in Fabric

Introduce yourself to the role of data engineering within the Fabric platform.

2. OneLake Introduction

Explore OneLake's features and how it integrates with the Microsoft Fabric ecosystem.

3. Lakehouse

Understand the Lakehouse methodology and its application in data management.

4. Delta Lake

Discover the capabilities of Delta Lake and its significance in data engineering.

5. OneLake Explorer

Take a tour of OneLake Explorer and its utilities for data exploration.

6. Authentication and Authorization

Examine the critical security aspects of authentication and authorization in Fabric.

7. Introduction to Shortcuts

Get to grips with the use of shortcuts for efficient navigation and operation within Fabric.

8. Creating Shortcuts

Learn the process of creating shortcuts to streamline your data engineering tasks.

9. Monitoring and Data Hubs

Understand how to monitor data hubs and maintain data integrity within Fabric.

10. Introduction to Lakehouse

Dive into an introduction of Lakehouse, setting the stage for advanced learning.

11. Lakehouse Architecture

Dissect the architecture of a Lakehouse and how it supports data management.

12. Lakehouse vs Warehouse

Compare and contrast Lakehouse with Warehouse architectures for informed decision-making.

13. What is Spark?

Explore what Spark is and how it revolutionizes data processing within Fabric.

14. Notebook Overview

This video introduces the core development tools in Microsoft Fabric, focusing on how data engineers can effectively use notebooks for data transformations and Spark job executions, with a hands-on approach to creating and connecting notebooks to lakehouses.

15. Web based and VS Code Notebooks

This video explores the development options available in VS Code for working with Microsoft Fabric notebooks, highlighting the process of downloading and setting up the VS Code editor, and addressing the current challenges and potential for future enhancements in the local development environment.

16. Spark and Monitoring Spark Jobs

Delve into the integration of Spark in monitoring and managing data jobs efficiently.

4. Data Warehouse

This section covers the A to Z of data warehousing in Microsoft Fabric, from the basics and data modeling to advanced data ingestion techniques using pipelines and dataflows. Enhance your proficiency in managing data within Fabric, executing cross-database queries, and creating insightful Power BI reports, all while mastering roles, permissions, and performance management for optimal data governance.

1. Introduction

Start with a primer on data warehousing concepts and their relevance in the data ecosystem.

2. Default Dataset and Modelling

Understand how to work with default datasets and their role in modeling within Fabric

3. Ingest Methods

Learn about various data ingestion methods and how to apply them in your work.

4. Load Data Introduction

Introduce the foundational steps for loading data into your Lakehouse.

5. Data loading into Lakehouse

Delve into the process of transferring data into the Lakehouse environment.

6. Load Data using Pipeline -Part 1

Discover the first part of using pipelines for data loading, setting the stage for advanced techniques.

7. Load Data using Dataflows

Understand how dataflows are used within Fabric for efficient data loading.

8. Load Data using Pipeline -Part 2

Continue learning about loading data using pipelines, enhancing your understanding and skills.

9. Models and Power BI Reports

Explore how to build models and generate Power BI reports from your data.

10. Cross-database Query

Learn how to execute cross-database queries within Fabric for comprehensive insights.

11. Roles and Permissions

Understand the roles and permissions framework within Fabric for effective data governance.

12. Performance Management

Focus on performance management to ensure your data solutions are optimized for efficiency.

5. Real-time Analytics

In this section, uncover the nuances of real-time analytics within Microsoft Fabric by comparing SQL with KQL, and deepening your understanding of KSQL databases and query sets. Gain practical knowledge of KSQLMagic and learn how Spark integrates with Fabric to empower your real-time data analysis.

1. SQL vs KQL

Compare SQL and KQL to understand their applications in real-time analytics.

2. Create, Process and Monitor

Learn how to create, process, and monitor real-time data processes within Fabric.

3. KSQL Queryset

Dive into the details of KSQL queryset and its applications in data analytics.

4. KSQL Database

Explore the structure and functions of a KSQL database for real-time data insights.

5. KSQLMagic

Get familiar with KSQLMagic and its role in enhancing real-time analytics operations.

6. Spark

Understand how Spark supports real-time analytics and its integration with Fabric.

6. Data Factory

Explore the full capabilities of Data Factory within Microsoft Fabric, from its core architecture and workspace setup to the intricacies of data flows, pipelines, and Gen2 transformations. Learn to automate and monitor data processes effectively with notebooks, script activities, and pipeline executions, all while navigating seamlessly between different Fabric workspaces.

1. What is Data Factory?

Discover what Data Factory is and its importance in the data management landscape

2. Data Flows and Pipelines

Examine the concepts of data flows and pipelines crucial for data operations.

3. Architecture

Delve into the architecture of Data Factory and how it fits into the larger ecosystem.

4. Workspace Setup

Learn the essentials of setting up your workspace for optimal use of Data Factory.

5. Control Table and Copy Data

Understand the role of the control table and the process of copying data within Fabric.

6. Metadata Copy Pattern

Explore the metadata copy pattern and its significance in data replication and management.

7. Script Activity

Learn about script activities and their application in automating data tasks.

8. Data Flows Gen2 Introduction

Introduce yourself to Gen2 data flows and their capabilities within Fabric.

9. Data Flows Gen2 Continuation

Continue your exploration of Gen2 data flows for a deeper understanding of their functionality.

10. Pipeline Execution

Gain insights into the execution of pipelines and how to manage them effectively.

11. Shortcut to Other Workspaces

Learn shortcuts to navigate between different workspaces efficiently within Fabric.

12. Notebooks

Explore how notebooks are used within Data Factory for data processing and analytics.

13. Data Flow Gen2 Transformations

Dive into the transformations possible with Data Flow Gen2 and their practical applications.

14. Pipelines, Notebooks and Parameters

Understand how pipelines, notebooks, and parameters work together to streamline data processes.

15. Notebooks Monitoring in Pipelines

Learn the best practices for monitoring notebooks within pipelines to ensure smooth operations.

7. Data Visualization with Power BI

This section delves into Power BI's integration with Microsoft Fabric, showcasing the enhanced interface, version control features for efficient change management, and the utilization of Direct Lake for real-time data insights within the Power BI environment.

1. Power BI and Fabric

This video introduces the integration of Power BI with Microsoft Fabric, highlighting its familiar yet evolved interface and the bundling with Azure Data Services, and addresses the new capabilities and changes for long-time Power BI users transitioning to Fabric.

2. Version Control

Learn about version control in Power BI to manage and track changes effectively.

3. Direct Lake

Understand the concept of Direct Lake and its application in Power BI for real-time insights.

8. Data Science

Uncover the essentials of data science within Microsoft Fabric, from a basic understanding to the detailed data science process and practical model management. Engage with exercises that reinforce learning and discover how to save and manage models effectively on the Fabric platform.

1. What is Data Science?

Get an introduction to the field of data science and its relevance in the modern data world.

2. Data Science Process

Dive into the data science process, from hypothesis to actionable insights.

3. Items and Models

Explore the various items and models used in data science within the Fabric platform.

4. Exercise

Engage in hands-on exercises to apply data science concepts practically.

5. Saving Models

Learn the process of saving models within Fabric for future use and reference.

6. Model Management

Delve into model management, an essential skill for any data scientist working with Fabric.

9. Data Management

This section introduces the fundamentals of data management in data-driven organizations, covering critical aspects such as access control for security, governance for integrity and compliance, and monitoring techniques for optimal data health and performance within the Fabric platform.

1. Introduction

Begin with an introduction to data management and its critical role in data-driven organizations.

2. Access Control

Gain an understanding of access control measures to secure your data environment.

3. Governance

Learn about governance principles to maintain data integrity and compliance.

4. Monitoring

Explore monitoring techniques to keep a pulse on your data's health and performance.

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Microsoft Fabric Complete Guide - The Future of Data with Fabric

By Packt

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