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Microsoft Certified: Fabric Analytics Engineer Associate

About this course

The Microsoft Certified: Fabric Analyst Engineer Associate has subject matter expertise in designing, creating, and managing analytical assets, such as semantic models, data warehouses, or lakehouses.

Instructor-Led Virtual Live Class

Exam DP-600: Implementing Analytics Solutions Using Microsoft Fabric

This is a role base certification exam. As a candidate for this exam, you should have subject matter expertise in designing, creating, and managing analytical assets, such as semantic models, data warehouses, or lakehouses.

Your responsibilities for this role include:

  • Prepare and enrich data for analysis
  • Secure and maintain analytics assets
  • Implement and manage semantic models

You work closely with stakeholders for business requirements and partner with architects, analysts, engineers, and administrators.

You should also be able to query and analyze data by using Structured Query Language (SQL), Kusto Query Language (KQL), and Data Analysis Expressions (DAX).

Requirements

Some experience with Power BI and/or Azure

Who this course is for:

  • A Power BI developer who wants to further increase their skills
  • An IT specialist (solution architect, database administrator, data scientist) of an organization where Power BI is being used
  • Anyone looking for additional ways to improve their understanding of Power BI and illustrate their knowledge by earning this new Microsoft certification

Course Outline

Implementing Analytics Solutions Using Microsoft Fabric

• Maintain a data analytics solution (25–30%)
• Prepare data (45–50%)
• Implement and manage semantic models (25–30%)

Maintain a data analytics solution (25–30%)

  • Implement workspace-level access controls
  • Implement item-level access controls
  • Implement row-level, column-level, object-level, and file-level access control
  • Apply sensitivity labels to items
  • Endorse items
  • Configure version control for a workspace
  • Create and manage a Power BI Desktop project (.pbip)
  • Create and configure deployment pipelines
  • Perform impact analysis of downstream dependencies from lakehouses, data warehouses, dataflows, and semantic models
  • Deploy and manage semantic models by using the XMLA endpoint
  • Create and update reusable assets, including Power BI template (.pbit) files, Power BI data source (.pbids) files, and shared semantic models

Prepare Data (45–50%)

  • Create a data connection
  • Discover data by using OneLake data hub and real-time hub
  • Ingest or access data as needed
  • Choose between a lakehouse, warehouse, or eventhouse
  • Implement OneLake integration for eventhouse and semantic models
  • Create views, functions, and stored procedures
  • Enrich data by adding new columns or tables
  • Implement a star schema for a lakehouse or warehouse
  • Denormalize data
  • Aggregate data
  • Merge or join data
  • Identify and resolve duplicate data, missing data, or null values
  • Convert column data types
  • Filter data
  • Select, filter, and aggregate data by using the Visual Query Editor
  • Select, filter, and aggregate data by using SQL
  • Select, filter, and aggregate data by using KQL

Implement and manage Semantic models (25–30%)

  • Choose a storage mode
  • Implement a star schema for a semantic model
  • Implement relationships, such as bridge tables and many-to-many relationships
  • Write calculations that use DAX variables and functions, such as iterators, table filtering, windowing, and information functions
  • Implement calculation groups, dynamic format strings, and field parameters
  • Identify use cases for and configure large semantic model storage format
  • Design and build composite models
  • Implement performance improvements in queries and report visuals
  • Improve DAX performance
  • Configure Direct Lake, including default fallback and refresh behavior
  • Implement incremental refresh for semantic models

  • Create and import a custom report theme
  • Create R or Python visuals in Power BI
  • Connect to and query datasets by using the XMLA endpoint
  • Design and configure Power BI reports for accessibility
  • Enable personalized visuals in a report
  • Configure automatic page refresh
  • Create and distribute paginated reports in Power BI Report Builder

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