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My learningPOWERBI Interview QuestionsLesson 06
Power BI Workflow: From Data Connection to Report Publishing

Lesson 06

Power BI Workflow: From Data Connection to Report Publishing

In Microsoft Power BI, the typical workflow starts with connecting to data sources, cleaning and transforming data using Power Query, building relationships and calculations with DAX, creating visual reports and dashboards in Power BI Desktop, and finally publishing the report to Power BI Service for sharing, collaboration, scheduling refreshes, and mobile access.

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Curriculum

21 lessons · 43m

0/21 lessons done43m left
  1. 0101:59

    What Is Power BI and What Business Problem Does It Solve?

    01:59

  2. 0202:05

    Main Components of Power BI Explained Simply

    02:05

  3. 0302:03

    Power BI Desktop vs Service vs Mobile: What’s the Difference?

    02:03

  4. 0401:53

    Power BI Licensing Explained: Free vs Pro vs PPU vs Fabric F-SKU

    01:53

  5. 0502:11

    PBIX vs PBIT in Power BI: What’s the Difference?

    02:11

  6. 02:07

    Power BI Workflow: From Data Connection to Report Publishing

    02:07

  7. 0702:06

    Power BI in Microsoft Fabric: Semantic Models and the New Unified Analytics Architecture

    02:06

  8. 0801:59

    Power BI Semantic Model vs Report vs Dashboard: What’s the Difference?

    01:59

  9. 0902:01

    Fact Table vs Dimension Table in Data Modeling Explained

    02:01

  10. 1002:12

    Star Schema in Power BI: Why It’s the Best Data Modeling Pattern

    02:12

  11. 1102:06

    Star Schema vs Snowflake Schema: What’s the Difference in Data Modeling?

    02:06

  12. 1201:57

    Power BI Relationship Cardinality: One-to-Many vs Many-to-Many Explained

    01:57

  13. 1302:00

    Single-Direction vs Bi-Directional Cross-Filtering in Power BI: When Should You Use Each?

    02:00

  14. 1401:58

    Active vs Inactive Relationships in Power BI: How to Use Inactive Relationships in Measures

    01:58

  15. 1501:53

    Role-Playing Dimensions in Power BI: How to Model Multiple Date Relationships Efficiently

    01:53

  16. 1602:15

    Normalized vs Denormalized Models in Power BI: Why Star Schemas Perform Better

    02:15

  17. 1702:19

    Power Query and M Language in Power BI: What Are They Used For?

    02:19

  18. 1802:05

    Power Query vs DAX in Power BI: When Should You Use Each?

    02:05

  19. 1902:00

    What is query folding, and why is it important for performance?

    02:00

  20. 2001:47

    What is the difference between Merge Queries and Append Queries

    01:47

  21. 2102:03

    What is a Power Query parameter, and give one real use case for it.

    02:03