Training Overview
As a candidate for this exam, you should have subject matter expertise in designing, creating, and managing analytical assets, such as semantic models, 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 analyse data by using Structured Query Language (SQL), Kusto Query Language (KQL), and Data Analysis Expressions (DAX).
Course Agenda
Implement security and governance
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
Maintain the analytics development lifecycle
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, 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
Get data
Create a data connection
Discover data by using OneLake catalogue and Real-Time hub
Ingest or access data as needed
Choose between different data stores
Implement OneLake integration for Eventhouse and semantic models