Fabric Analytics Engineer Bootcamp

Have you ever dreamed of becoming an Analytics Engineer and mastering the most in-demand skills in today’s data analytics ecosystem? This course will boost your career opportunities in the analytics realm, while at the same time setting you ready for acquiring the popular DP-600 certificate (Microsoft Fabric Analytics Engineer). You’ll learn the skills necessary to succeed as an Analytics Engineer, and how to practically apply these skills by using Microsoft Fabric!

This course includes practical examples that any Analytics Engineer can immediately apply in their day-to-day job, and many useful tips specifically related to successfully passing the DP-600 exam.

 

Agenda

  1. Introduction
    1. Tutorial overview
    2. Goals and outcomes
    3. Setting the expectations
  2. Microsoft Fabric Core Components
    1. Fabric – unified platform, tools, people who work with Fabric
    2. OneLake
    3. Different Fabric engines
    4. Delta format as a key pillar of Fabric
  3. Prepare and Serve Data in Microsoft Fabric – Creating Fabric Items
    1. Create a lakehouse and/or a warehouse
    2. Ingest data with notebooks, pipelines and Dataflows Gen2
    3. Create and manage shortcuts
    4. Create views and stored procedures
  4. Prepare And Serve Data in Microsoft Fabric – Data Orchestration
    1. Understand methods to copy the data from data source to Fabric
    2. Implement data orchestration with Fabric pipelines
  5. Prepare And Serve Data in Microsoft Fabric – Data Modeling
    1. Understand basic dimensional modeling concepts
    2. Understand fact and dimension tables
    3. Implement normalization and denormalization
    4. Aggregate the data
    5. Implement a star or snowflake schema
    6. Understand medallion architecture
    7. Implement medallion architecture in Fabric lakehouse
  6. Prepare And Serve Data in Microsoft Fabric – Data Transformation
    1. Implement data cleaning
    2. Apply data profiling with Notebooks and Dataflows Gen2
    3. Enhance semantic models with additional columns
  7. Prepare And Serve Data in Microsoft Fabric – Performance Optimization
    1. Identify data loading performance bottlenecks
    2. Understand the concept of query folding
    3. Implement performance optimization techniques in Dataflows Gen2 and notebooks
  8. Design Semantic Models
    1. Understand different storage modes (Import, DirectQuery, Direct Lake)
    2. Understand the difference between default and custom semantic models
    3. Enhance semantic models with DAX calculations
    4. Implement advanced semantic model features, such as Calculation Groups and Field Parameters
    5. Implement composite models, including Power BI aggregations
    6. Implement and validate RLS and OLS
  9. Optimizing Semantic Model Performance
    1. Troubleshoot poorly performing DAX queries with DAX Studio
    2. Optimize semantic model with Tabular Editor 2
    3. Implement Incremental refresh
  10. Configure and Manage the Fabric Environment
    1. Understand settings in the Fabric Admin portal
    2. Understand workspace roles and permissions
    3. Fabric licensing options
    4. Implement and manage version control for the Fabric workspace
    5. Manage and deploy semantic models by using XMLA endpoint
  11. Explore and Analyze Data
    1. Apply descriptive analytics in Microsoft Fabric
    2. Understand T-SQL window functions
    3. Query data in the lakehouse by using notebooks
    4. Query data in the lakehouse/warehouse by using T-SQL
    5. Query data by using XMLA endpoint
  12. Practical Exam Tips, Quiz and Closing
    1. How to prepare for the exam – practical tips, tricks and recommendations
    2. Quiz

 

Prerequisites:

  • Experience with any BI tool, preferably Microsoft’s stack
  • Basic understanding of data modeling
  • Foundational knowledge of relational databases
  • Experience with Microsoft Power BI
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