Saturday 13 January 2024

Can you explain a few ways of how a Power Query can transform the data in Power BI ?Power BI interview questions and answers 395

Can you explain a few ways of how a Power Query can transform the data in Power BI ? 

Here are several ways Power Query can transform data in Power BI, making it ready for analysis and visualization:

1. Data Shaping:

  • Remove or Add Columns: Select or deselect columns to include in your model.

  • Filter Rows: Keep only relevant data based on specific criteria.

  • Sort Data: Arrange rows in a desired order.

  • Rename Columns: Assign meaningful names for clarity.

  • Change Data Types: Ensure accurate interpretation of data (e.g., text, numbers, dates).

2. Data Cleaning:

  • Handle Missing Values: Fill gaps with default values or remove rows with missing data.

  • Correct Errors: Fix inconsistencies or inaccuracies in values.

  • Remove Duplicates: Eliminate redundant rows.

  • Standardize Formatting: Ensure consistency in data presentation.

3. Data Aggregation:

  • Group Data: Combine rows based on shared values for summary calculations.

  • Calculate Totals: Sum, average, count, or apply other aggregations to grouped data.

4. Data Transformation:

  • Split Columns: Divide a column into multiple columns based on delimiters or patterns.

  • Combine Columns: Merge multiple columns into a single column.

  • Extract Text: Extract specific portions of text from columns.

  • Apply Conditional Logic: Create new columns or modify existing ones based on conditions.

5. Data Enhancement:

  • Add Calculated Columns: Create new columns with formulas to derive insights or manipulate data.

  • Merge Tables: Combine data from multiple sources into a single table.

  • Append Queries: Add more rows to an existing table from another source.

  • Apply Custom Functions: Use M language for advanced data transformations.

6. Data Connection Management:

  • Manage Data Sources: Connect to various data sources (databases, Excel files, web services, etc.).

  • Set Refresh Schedules: Automate data updates to ensure freshness.

  • Optimize Performance: Adjust query settings for efficient data retrieval.

Remember: Power Query's transformations are applied before loading data into the Power BI model, ensuring you work with clean, structured, and analysis-ready data.

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