Microsoft Learn

• Study guide for Exam DP-600: Implementing Analytics Solutions Using Microsoft Fabric (opens in a new tab)

Exam Topics

Plan, implement, and manage a solution for data analytics (10–15%)

Plan a data analytics environment

• Identify requirements for a solution, including components, features, performance, and capacity stock-keeping units (SKUs)
• Recommend settings in the Fabric admin portal
• Choose a data gateway type
• Create a custom Power BI report theme

Implement and manage a data analytics environment

• Implement workspace and item-level access controls for Fabric items
• Implement data sharing for workspaces, warehouses, and lakehouses
• Manage sensitivity labels in semantic models and lakehouses
• Configure Fabric-enabled workspace settings
• Manage Fabric capacity

Manage the analytics development lifecycle

• Implement version control for a workspace
• Create and manage a Power BI Desktop project (.pbip)
• Plan and implement deployment solutions
• 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 and serve data (40–45%)

Create objects in a lakehouse or warehouse

• Ingest data by using a data pipeline, dataflow, or notebook
• Create and manage shortcuts
• Implement file partitioning for analytics workloads in a lakehouse
• Create views, functions, and stored procedures
• Enrich data by adding new columns or tables

Copy data

• Choose an appropriate method for copying data from a Fabric data source to a lakehouse or warehouse
• Copy data by using a data pipeline, dataflow, or notebook
• Add stored procedures, notebooks, and dataflows to a data pipeline
• Schedule data pipelines
• Schedule dataflows and notebooks

Transform data

• Implement a data cleansing process
• Implement a star schema for a lakehouse or warehouse, including Type 1 and Type 2 slowly changing dimensions
• Implement bridge tables for a lakehouse or a warehouse
• Denormalize data
• Aggregate or de-aggregate data
• Merge or join data
• Identify and resolve duplicate data, missing data, or null values
• Convert data types by using SQL or PySpark
• Filter data

Optimize performance

• Identify and resolve data loading performance bottlenecks in dataflows, notebooks, and SQL queries
• Implement performance improvements in dataflows, notebooks, and SQL queries
• Identify and resolve issues with Delta table file sizes

Implement and manage semantic models (20–25%)

Design and build semantic models

• Choose a storage mode, including Direct Lake
• Identify use cases for DAX Studio and Tabular Editor 2
• 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 strings, and field parameters
• Design and build a large format dataset
• Design and build composite models that include aggregations
• Implement dynamic row-level security and object-level security
• Validate row-level security and object-level security

Optimize enterprise-scale semantic models

• Implement performance improvements in queries and report visuals
• Improve DAX performance by using DAX Studio
• Optimize a semantic model by using Tabular Editor 2
• Implement incremental refresh

Explore and analyze data (20–25%)

Perform exploratory analytics

• Implement descriptive and diagnostic analytics
• Integrate prescriptive and predictive analytics into a visual or report
• Profile data

Query data by using SQL

• Query a lakehouse in Fabric by using SQL queries or the visual query editor
• Query a warehouse in Fabric by using SQL queries or the visual query editor
• Connect to and query datasets by using the XMLA endpoint

Services

Power Query

Dataflows (Gen2)

Azure Data Factory

• Managed, serverless ETL/ELT service
• SSIS (SQL Server Integration Services) in the cloud

Azure Data Factory - Data Factory Pipelines

Data Factory Pipelines can be used to orchestrate Spark, Dataflow, and other activities; enabling you to implement complex data transformation processes.

Microsoft Fabric

• Pricing (opens in a new tab)

Capacity

• Key points

  • A Microsoft Fabric capacity resides on a tenant.
  • Each capacity that sits under a specific tenant is a distinct pool of resources allocated to Microsoft Fabric.

• Benefits

  • Centralized management of capacity

    Rather than provisioning and managing separate resources for each workload, with Microsoft Fabric, your bill is determined by 2 variables:

    • The amount of compute you provision

      • A shared pool of capacity that powers all capabilities in Microsoft Fabric.
      • Pay-as-you-go and 1-year Reservation

    • The amount of storage you use

      • A single place to store all data
      • Pay-as-you-go (billable per GB/month)

Capacity License SKUs

• Capacity licenses are split into SKUs. Each SKU provides a set of Fabric resources for your organization. Your organization can have as many capacity licenses as needed.

Capacity Unit

• Capacity unit (CU) = Compute Power

• CU Consumption

  Each capability, such as Power BI, Spark, Data Warehouse, with the associated queries, jobs, or tasks has a unique consumption rate.

Access Control

• Tenant

• Capacity

• Workspace

• Item

  Data Warehouse, Data Lakehouse, Dataflow, Semantic Model, etc.

• Object

  Table, View, Function, Stored Procedure, etc.

Workspace

• Workspace is created under a capacity.
• Workspace is a container for Microsoft Fabric items.

Workspace - License mode

• Microsoft Learn - Microsoft Fabric concepts and licenses (opens in a new tab)

• The workspace license mode dictates what kind of capacity the workspace can be hosted in and as a result the capabilities available.

Workspace - Roles

• Workspace roles apply to all items in the workspace

• Roles in workspaces in Microsoft Fabric (opens in a new tab)

• Admin

  • Update and delete the workspace
  • Add or remove people, including other admins

• Member

  Everything an admin can do, except the above two.

  • Add members or others wtith lower permissions
  • Allow others to reshare items

• Contributor

  Everything a member can do, except the above two.

• Viewer

  Read-only access to the workspace without API access.