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• Data science: it is the process or technology that encompasses various tasks and processes required to convert raw data into actionable insights and build efficient data models to solve business problems.
• Big data: Big data refers to the huge amounts of data that act as the fuel for data science models. These data can be in petabytes or zettabytes
• �Data analytics: it is the process of all the statistical and mathematical processing required to identify trends and patterns within the data.

1. Load Data:Import your data source into Power BI using the "Get Data" option. You can connect to various sources like Excel, CSV, SQL databases, and more.
2. Edit Query:Once your data is loaded, right-click on the query name and select "Edit Query." This will open the Power Query Editor where you can apply transformations.
3. Apply Transformations:Use the available functions and operators in Power Query M to perform transformations like:
   • Cleaning:Remove duplicates, handle null values, and correct data types.
   • Combining:Merge multiple tables based on common columns.
   • Reshaping:Pivot or unpivot columns, add or remove columns.
   • Filtering:Apply conditions to extract specific data.
   • Sorting:Arrange data in ascending or descending order.
   • Grouping:Group data by specific columns and calculate aggregations.
4. Apply Steps:As you apply transformations, Power Query M generates a series of steps. You can edit or delete these steps to refine your data.
5. Close and Apply:When you're satisfied with the transformations, click "Close & Apply" to apply the changes to your Power BI report.

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