How to Load from a Folder Without Combining Files in Power BI
In the realm of data analytics, Power BI stands out for its robustness and versatility. One common task involves importing data from files stored in a folder. By default, Power BI tends to combine all these files into a single table, which might not always align with your project’s requirements. This article explores a workaround for loading each file into its own table without combining them, a critical skill for managing distinct data sets more effectively.
Why Load Files Separately?
Loading each file into its own table can be essential for several reasons:
- Data Segregation: Different files might represent data for different periods, regions, or categories. Keeping them in separate tables helps maintain their distinctness.
- Data Volume: Combining large files might lead to performance issues. Separating files can mitigate this concern.
- Custom Processing: Certain files may require unique processing steps or transformations. Loading them separately facilitates this customization.
Step-by-Step Guide: How to Achieve Separate Loading
Step 1: Folder Source Connection
Initially, you might opt to ‘Get Data’ from a folder, expecting Power BI to offer an option to load files individually. When it combines files by default, here is what you can do instead:
- Go to ‘Get Data’ and choose ‘Text/CSV’ instead of ‘Folder’.
- Browse to the directory where your files are located but do not select any file. Note the path from the address bar.
Step 2: Query Editor Magic
- From ‘Home’, choose ‘New Source’, then ‘Blank Query’.
- In the formula bar, type
= Folder.Files("YourFolderPathHere")
, replacing YourFolderPathHere
with the path you noted before. This action creates a list of the files in that folder.
- You will now see a table listing all files in the Query Editor.
Step 3: Custom Function Creation
- To load each file into its own table without combining them, we will leverage Power BI’s ‘Invoke Custom Function’ feature.
- In the Query Editor, right-click your query and navigate to ‘Create Function’. This might prompt you to choose sample file parameters but you can proceed without selecting any.
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Step 4: Import Files Individually
- Now, add a column to your query by right-clicking and selecting ‘Add Column’ -> ‘Invoke Custom Function’.
- Name your new column, select the function you created in the previous step, and for the ‘File Path’ parameter, choose the ‘Content’ column.
- This process essentially runs your function across each row (file), loading each as its own table based on the custom function’s instructions.
Step 5: Data Transformation (Optional)
- At this stage, each file has been loaded into its own table. You might need to apply additional transformations or processing to these tables.
- Apply these transformations as you normally would for single datasets within the Power BI Query Editor.
Step 6: Loading into Power BI
- Once you've completed your transformations, choose ‘Close & Apply’ from the Home tab to load your data into Power BI.
- You will now have each file loaded as a separate table within your Power BI model, enabling distinct analysis and reporting activities.
Real-World Example
Imagine managing sales data from multiple regions, where each region's data is stored in a separate file within a shared folder. By loading these files individually, you can create a regional analysis dashboard that segments data accordingly, enhancing insights and decision-making processes.
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Conclusion
Power BI’s default behavior to combine files from a folder into a single table might not be suitable for all analytical tasks. By following the above steps, you’ll be able to bypass this default setting, loading each file into its own table, which broadens your analytical capabilities. This approach not only enhances data management and processing versatility but also ensures that your reporting and analytics can be customized to the unique requirements of each dataset.
Whether you're managing diverse data sets or require specialized processing for each file, this method opens up new possibilities for data analysis in Power BI. Remember, tools like Flowpoint.ai can further enhance your analytics endeavors by pinpointing and addressing conversion rate impediments, marrying data-driven insights with actionable recommendations.