Thursday 21 December 2023

What is the difference between Direct Query and SQL Server import in ? Power BI interview questions and answers 075

What is the difference between Direct Query and SQL Server import in ? 

Here's a detailed explanation of the differences between DirectQuery and SQL Server import in Power BI:

Data Storage and Handling:

  • Import:

  • Copies data from the SQL Server database into the Power BI file.

  • Stores data locally within the file, creating a compressed dataset.

  • Uses local processing for visualizations and calculations.

  • DirectQuery:

  • Keeps data in the SQL Server database.

  • Queries data directly from the source on-demand when interacting with visualizations.

  • Relies on the source database for processing queries.


  • Import:

  • Often faster for interactive visualizations and calculations due to local data storage and processing.

  • Initial import can take time for large datasets.

  • DirectQuery:

  • Performance depends on the underlying database performance and network connectivity.

  • Can be slower for complex visualizations or large datasets, as queries are sent to the database each time.

Data Refresh:

  • Import:

  • Requires manual or scheduled refreshes to update the dataset with new data from the source.

  • DirectQuery:

  • Displays the most up-to-date data without manual refreshes, as it queries the source directly.

Data Transformations:

  • Import:

  • Allows extensive data transformations and shaping using Power Query before importing.

  • DirectQuery:

  • Limited to transformations supported by the SQL Server database and its query language.

  • Complex transformations might need to be performed in the database itself.

Data Modeling:

  • Import:

  • More flexibility in creating complex data models with multiple relationships and measures.

  • DirectQuery:

  • Certain modeling features might be restricted or unavailable due to reliance on the source database's capabilities.

Use Cases:

  • Import:

  • Ideal for smaller to medium-sized datasets with frequent interactivity and analysis.

  • Suitable when extensive data transformations or complex modeling are required.

  • DirectQuery:

  • Better for very large datasets or near-real-time data visualization.

  • Preferred when showcasing the latest data from a frequently changing source.

  • Useful when direct database access is necessary for security or compliance reasons.

Choosing the Right Method:

The best choice depends on your specific needs, considering factors like:

  • Dataset size

  • Data refresh frequency

  • Performance requirements

  • Data transformation needs

  • Data modeling complexity

  • Security and compliance considerations

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