⚡Power BI

Features

  • architecture
    • XMLA read/write
      • enable XMLA endpoints
    • separation of data and content: Martens
  • data gateway
  • data visuals
  • dataflows
    • best practices: Microsoft
    • streaming: Microsoft
    • perform in-storage computations
    • optimize the use of dataflows
    • use incremental refresh with dataflows
    • reference other dataflows
  • datamarts: Microsoft
  • datasets
  • architecture
    • Power BI enhanced report format (PBIR): Romano
  • DAX
    • DAX query view: Microsoft
    • visual calculations
    • calculation groups
    • controlling selections: SQLBI
  • infrastructure
    • autoscale
    • backup and restore
    • multi-geo: Microsoft
    • Report Server
    • storage
  • insights
  • semantic models 
  • time intelligence
    • filtering weekdays: SQLBI

    Actions

    DAX Functions

    Power BI Challenges
    Power BI Tools
    Power Query Functions
    Resources
    References:

    Certifications

    Exam PL-300: Microsoft Power BI Data Analyst [study guide]
    • Prepare the data (25–30%)
      • Get or connect to data
        • Identify and connect to data sources or a shared semantic model
        • Change data source settings, including credentials and privacy levels
        • Choose between DirectQuery and Import
        • Create and modify parameters
      • Profile and clean the data
        • Evaluate data, including data statistics and column properties
        • Resolve inconsistencies, unexpected or null values, and data quality issues
        • Resolve data import errors
      • Transform and load the data
        • Select appropriate column data types
        • Create and transform columns
        • Group and aggregate rows
        • Pivot, unpivot, and transpose data
        • Convert semi-structured data to a table
        • Create fact tables and dimension tables
        • Identify when to use reference or duplicate queries and the resulting impact
        • Merge and append queries
        • Identify and create appropriate keys for relationships
        • Configure data loading for queries
    • Model the data (25–30%)
      • Design and implement a data model
        • Configure table and column properties
        • Implement role-playing dimensions
        • Define a relationship's cardinality and cross-filter direction
        • Create a common date table
        • Identify use cases for calculated columns and calculated tables
      • Create model calculations by using DAX
        • Create single aggregation measures
        • Use the CALCULATE function
        • Implement time intelligence measures
        • Use basic statistical functions
        • Create semi-additive measures
        • Create a measure by using quick measures
        • Create calculated tables or columns
        • Create calculation groups
      • Optimize model performance
        • Improve performance by identifying and removing unnecessary rows and columns
        • Identify poorly performing measures, relationships, and visuals by using Performance Analyzer and DAX query view
        • Improve performance by reducing granularity
      • Visualize and analyze the data (25–30%)
        • Create reports
        • Select an appropriate visual
        • Format and configure visuals
        • Apply and customize a theme
        • Apply conditional formatting
        • Apply slicing and filtering
        • Configure the report page
        • Choose when to use a paginated report
        • Create visual calculations by using DAX
      • Enhance reports for usability and storytelling
        • Configure bookmarks
        • Create custom tooltips
        • Edit and configure interactions between visuals
        • Configure navigation for a report
        • Apply sorting to visuals
        • Configure sync slicers
        • Group and layer visuals by using the Selection pane
        • Configure drill through navigation
        • Configure export settings
        • Design reports for mobile devices
        • Enable personalized visuals in a report
        • Design and configure Power BI reports for accessibility
        • Configure automatic page refresh
      • Identify patterns and trends
        • Use the Analyze feature in Power BI
        • Use grouping, binning, and clustering
        • Use AI visuals
        • Use reference lines, error bars, and forecasting
        • Detect outliers and anomalies
    • Manage and secure Power BI (15–20%)
      • Create and manage workspaces and assets
        • Create and configure a workspace
        • Configure and update a workspace app
        • Publish, import, or update items in a workspace
        • Create dashboards
        • Choose a distribution method
        • Configure subscriptions and data alerts
        • Promote or certify Power BI content
        • Identify when a gateway is required
        • Configure a semantic model scheduled refresh
      • Secure and govern Power BI items
        • Assign workspace roles
        • Configure item-level access
        • Configure access to semantic models
        • Implement row-level security roles
        • Configure row-level security group membership
        • Apply sensitivity labels
    Books
    • Nagaraj Venkatesan (2025) Architecting Power BI Solutions in Microsoft Fabric [PacktPub]
    • Greg Deckler & Brett Powell (2024) Microsoft Power BI Cookbook 3rd Ed. [PacktPub, GitHub]
    • Thomas LeBlanc & Bhavik Merchant (2024) Microsoft Power BI Performance Best Practices 2nd Ed. [PacktPub, GitHub] >
    • Sandielly Ortega Polanco et al (2024) The Complete Power BI Interview Guide[PacktPub, GitHub]
    • Daniil Maslyuk (2023) Exam Ref PL-300 Microsoft Power BI Data Analyst [GitHub incl. labs]

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    Koeln, NRW, Germany
    IT Professional with more than 25 years experience in IT in the area of full life-cycle of Web/Desktop/Database Applications Development, Software Engineering, Consultancy, Data Management, Data Quality, Data Migrations, Reporting, ERP implementations & support, Team/Project/IT Management, etc.