Power BI Interview Questions and Answers for 10 years experience

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100 Power BI Interview Questions & Answers (10 Years Experience)

  1. What are the key differences between Power BI Desktop and Power BI Service?

    • Answer: Power BI Desktop is a free application for creating and shaping data models, while Power BI Service is a cloud-based service for sharing and collaborating on reports and dashboards. Desktop focuses on data modeling and report creation, while the Service handles publishing, sharing, collaboration, data refresh, and user management.

  2. Explain the different types of data sources that Power BI can connect to.

    • Answer: Power BI connects to a vast array of data sources, including relational databases (SQL Server, Oracle, MySQL), cloud databases (Azure SQL Database, Snowflake, Google BigQuery), Excel files, CSV files, text files, web services (OData, REST APIs), and many more. It also supports direct connections to various SaaS applications like Salesforce, Dynamics 365, and SharePoint.

  3. Describe the different data modeling techniques used in Power BI.

    • Answer: Key techniques include star schema (fact and dimension tables), snowflake schema (normalized dimension tables), and data warehousing techniques. Understanding data relationships, creating hierarchies, and using calculated columns and measures are crucial.

  4. What are DAX measures and how are they different from calculated columns?

    • Answer: DAX (Data Analysis Expressions) measures are calculations performed at the report level, dynamically updating based on the applied filters. Calculated columns are calculated at the row level during data import and are static unless the data source is refreshed. Measures are ideal for dynamic aggregations, while calculated columns are better for adding derived attributes to the data model.

  5. Explain the role of Power Query (Get & Transform Data) in Power BI.

    • Answer: Power Query is used for data cleaning, transformation, and loading. It allows users to connect to various data sources, clean and shape data using various functions (like filtering, sorting, merging, pivoting), and load it into the Power BI data model. It significantly improves data quality and efficiency.

  6. How do you handle large datasets in Power BI?

    • Answer: Techniques include direct query mode (connecting directly to the source database), using DirectQuery with composite models (combining DirectQuery and import), optimizing data model design (using appropriate data types, efficient relationships), using Power BI dataflows for data preparation, and implementing data sampling or aggregation.

  7. What are the different types of visualizations available in Power BI?

    • Answer: Power BI offers a wide variety of visualizations including charts (bar, column, line, pie, scatter), maps, tables, matrices, cards, gauges, and custom visuals from the AppSource marketplace. The choice depends on the type of data and the insights to be conveyed.

  8. Explain the concept of row-level security (RLS) in Power BI.

    • Answer: RLS allows restricting data access at the row level based on user context (e.g., department, role). It ensures that users only see the data relevant to them, enhancing data security and privacy.

  9. How do you create and manage dataflows in Power BI?

    • Answer: Dataflows are created in the Power BI service and are used for data preparation and transformation at scale. They can connect to various data sources, perform data cleaning and transformation using Power Query, and store the transformed data in a common data service (CDS) for use across multiple reports and datasets.

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