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Analyze data in Azure Data Lake Storage Gen1 by using Power BI

In this article, you learn how to use Power BI Desktop to analyze and visualize data stored in Azure Data Lake Storage Gen1.

Prerequisites

Before you begin this tutorial, you must have the following:

Create a report in Power BI Desktop

  1. Launch Power BI Desktop on your computer.

  2. From the Home ribbon, click Get Data, and then click More. In the Get Data dialog box, click Azure, click Azure Data Lake Store, and then click Connect.

    Screenshot of the Get Data dialog box with the Azure Data Lake Store option highlighted and the Connect option called out.

  3. If you see a dialog box about the connector being in a development phase, opt to continue.

  4. In the Azure Data Lake Store dialog box, provide the URL to your Data Lake Storage Gen1 account, and then click OK.

    URL for Data Lake Storage Gen1

  5. In the next dialog box, click Sign in to sign into the Data Lake Storage Gen1 account. You will be redirected to your organization's sign-in page. Follow the prompts to sign into the account.

    Sign into Data Lake Storage Gen1

  6. After you have successfully signed in, click Connect.

    Screenshot of the Azure Data Lake Store dialog box with the Connect option called out.

  7. The next dialog box shows the file that you uploaded to your Data Lake Storage Gen1 account. Verify the info and then click Load.

    Load data from Data Lake Storage Gen1

  8. After the data has been successfully loaded into Power BI, you will see the following fields in the Fields tab.

    Imported fields

    However, to visualize and analyze the data, we prefer the data to be available per the following fields

    Desired fields

    In the next steps, we will update the query to convert the imported data in the desired format.

  9. From the Home ribbon, click Edit Queries.

    Screenshot of the Home ribbon with the Edit Queries option called out.

  10. In the Query Editor, under the Content column, click Binary.

    Screenshot of the Query Editor with the Content column called out.

  11. You will see a file icon, that represents the Drivers.txt file that you uploaded. Right-click the file, and click CSV.

    Screenshot of the Query Editor with the CSV option called out.

  12. You should see an output as shown below. Your data is now available in a format that you can use to create visualizations.

    Screenshot of the Query Editor with the output displayed as expected.

  13. From the Home ribbon, click Close and Apply, and then click Close and Apply.

    Screenshot of the Home ribbon with the close and Apply option called out.

  14. Once the query is updated, the Fields tab will show the new fields available for visualization.

    Updated fields

  15. Let us create a pie chart to represent the drivers in each city for a given country/region. To do so, make the following selections.

    1. From the Visualizations tab, click the symbol for a pie chart.

      Create pie chart

    2. The columns that we are going to use are Column 4 (name of the city) and Column 7 (name of the country/region). Drag these columns from Fields tab to Visualizations tab as shown below.

      Create visualizations

    3. The pie chart should now resemble like the one shown below.

      Pie chart

  16. By selecting a specific country/region from the page level filters, you can now see the number of drivers in each city of the selected country/region. For example, under the Visualizations tab, under Page level filters, select Brazil.

    Select a country/region

  17. The pie chart is automatically updated to display the drivers in the cities of Brazil.

    Drivers in a country/region

  18. From the File menu, click Save to save the visualization as a Power BI Desktop file.

Publish report to Power BI service

Once you have created the visualizations in Power BI Desktop, you can share it with others by publishing it to the Power BI service. For instructions on how to do that, see Publish from Power BI Desktop.

See also