Advanced Power BI MasterClass

ADVANCED POWER BI – COURSE OUTLINE

Section 1: Data analytics With Power BI

• Understanding data analytics
• Explore Roles in data Analysis
• Key Tasks for a data analyst
• Introduction to Power BI Desktop Advanced Features
• Components of Power BI
• Understanding Power BI Services

Section 2: Design a data model in Power BI

• Get data from files & folders
  

  

• Get data from relational data sources
• Get data from a NoSQL database
• Get data from online services
• Select a storage mode
• Get data from Azure Analysis Services
• Fix performance issues
• Resolve data import errors
• Understanding Constraints & Performance issues
• Understand data types mismatch issues
• Resolving data quality errors

Section 3: Data Cleansing With Power BI

• Shape the initial data
• Simplify the data structure
• Evaluate and change column data types
• Combine multiple tables into a single table
• Profile data in Power BI
• Use Advanced Editor to modify M code

Section 4: Creating Advanced DAX measures in Power BI

• Using the Calculate function
• Understanding Filter Context
• Using IF, SWITCH, FIND
• Using VALUES, HASONEVALUE, SELECTEDVALUE, and CONCATENATEX
• Using ALL, ALLEXCEPT, ALLSELECTED, KEEPFILTERS
• Creating Virtual Tables
• Create semi-additive measures
• Advanced Date Comparisons With Same Period Last Year, Year To Date, Month to date totals,
• Using Date Functions like DATEADD, FIRSTDATE, LASTDATE, NEXTYEAR
• Writing Custom Time Intelligence Functions
• Using RELATED & RELATEDTABLE functions in Power BI

Section 5: Performance Optimization in Power BI

• Performance optimization Considerations
• Review performance of Measures, Relationships, and visuals
• Using variables to improve performance & Troubleshooting
• Reduce cardinality in the Data Model
• Optimize DirectQuery models with table level storage
• Create and manage aggregations

Section 6: Working with Power BI visuals

• Introduction to Advanced Power BI visualizations
• Add visualization items to reports
• Choose an effective visualization
• Format and configure visualizations
• Import a custom visual into Power BI
• Add an R or PYTHON visual in a report

Section 7: Create a data-driven story with Power BI reports

• Introduction to create a data-driven story with Power BI reports
• Design a report layout
• Add buttons, bookmarks, and selections
• Design report navigation
• Use advanced interactions and drill through
• Configure conditional formatting
• Apply slicing, filtering, and sorting
• Publish and export reports
• Comment on reports
• Fine Tune report performance
• Optimize reports for mobile use

Section 8: Create dashboards in Power BI

• Introduction to dashboards
• Configure data alerts
• Explore data by asking questions
• Add a dashboard theme
• Pin a live report page to a dashboard
• Configure a real-time dashboard
• Configure data classification
• Explore mobile view & Auto Mobile Layouts

Section 9: Perform analytics in Power BI

• Introduction to analytics
• Explore statistical summary
• Identify outliers with Power BI visuals
• Group and bin data for analysis
• Apply clustering techniques
• Conduct time series analysis
• Use the Analyze feature
• Use advanced analytics custom visuals
• Review Quick insights
• Apply AI Insights

Section 10: Work with AI visuals in Power BI

• Introduction to working with AI visuals
• Use the Q&A visual
• Find important factors with the Key influencers visual
• Use the Decomposition Tree visual to break down a measure

Section 11: Create and manage workspaces in Power BI

• Distribute a report or dashboard
• Monitor usage and performance
• Recommend a development life cycle strategy
• Troubleshoot data by viewing its lineage
• Configure data protection

Section 12: Secure Access With Row-Level Security

• Configure row-level security with the static method
• Configure row-level security with the dynamic method

Section 13: Manage datasets in Power BI

• Create dynamic reports with parameters
• Create what-if parameters
• Use a Power BI gateway to connect to on-premises data sources
• Configure a dataset scheduled refresh
• Configure incremental refresh settings
• Manage and promote datasets
• Troubleshoot service connectivity