Curriculum
3 Sections
24 Lessons
45 Hours
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Introduction to Power BI
15
1.1
Exploring & Analyzing Data
1.2
Describe Power BI Desktop models (star schema, analytic queries, report visuals)
1.3
Choose a model framework (Import, DirectQuery, Composite Models)
1.4
Design a semantic model (tables, date tables, dimensions, relationships, cardinality)
1.5
Write advanced DAX formulas (functions, operators, variables)
1.6
Add measures (simple, compound, quick measures, calculated columns)
1.7
Use DAX time intelligence functions (time intelligence, advanced calculations)
1.8
Optimize model performance
1.9
Enforce model security
1.10
Sharing Insights:
1.11
Scope report design requirements (audience, report types, UI/UX requirements)
1.12
Design Power BI reports (layout, visuals, KPIs)
1.13
Configure report filters (designing for filtering, advanced techniques)
1.14
Enhance report designs (details, highlighting values, navigation)
1.15
Perform analytics in Power BI (statistical summary, outliers, clustering, time series, AI visuals)
Dashboarding and Storytelling
4
2.1
Create and manage workspaces and dashboards
2.2
Manage semantic models (connect to on-premises data, query caching)
2.3
Create dashboards (data alerts, Quick insights)
2.4
Implement row-level security (static and dynamic)
Python in Power BI
5
3.1
Run Python scripts in Power BI Desktop
3.2
Use Python in Power Query Editor
3.3
Use an external Python IDE with Power BI
3.4
Create Power BI visuals with Python
3.5
Learn which Python packages are supported in Power BI
Power BI Pro: Advanced Analytics and Business Intelligence (Level 2)
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