Do not treat this objective as a recognition exercise. Practise explaining and applying 'Maintain the analytics development lifecycle: Deploy and manage semantic models by using the XMLA endpoint' in a new scenario, then check your reasoning against the official source. Source context: Read in English Manage the semantic model development lifecycle Module 9 Units Feedback Intermediate Data Analyst Power BI Microsoft Fabric Manage semantic models through their full development lifecycle. Create reusable assets, version-control with Git, inspect and validate with the XMLA endpoint and SemPy, deploy through pipelines, and maintain with monitoring and impact analysis. Learning objectives By the end of this module, you'll be able to: Create reusable Power BI assets Manage Power BI content in version control Manage semantic models with the XMLA endpoint Deploy content through stages Maintain and monitor semantic models Add Prerequisites Experience with Power BI Desktop and the Power BI service Understanding of semantic model concepts Familiarity with Python and Fabric notebooks, including DataFrames Foundational Git workflow knowledge (fork, branch, commit, sync, merge, pull request) Introduction min Create reusable Power BI assets min Manage Power BI content in version control min Manage semantic models with the XMLA endpoint min Deploy content through stages min Maintain and monitor semantic models min Exercise: Manage semantic models through their lifecycle min Module assessment min Summary min Take the module assessment Module Assessment Results Assess your understanding of this module.
Objective
Maintain the analytics development lifecycle: Deploy and manage semantic models by using the XMLA endpoint