Document Details
Hdinsight Sales Insights Etl
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This page contains Windows bias
About This Page
This page is part of the Azure documentation. It contains code examples and configuration instructions for working with Azure services.
Bias Analysis
Bias Types:
⚠️
powershell_heavy
⚠️
windows_tools
⚠️
windows_first
Summary:
The documentation provides both Bash (Linux/macOS) and Azure CLI examples for most operations, but when it comes to triggering the Azure Data Factory pipeline, it gives a detailed PowerShell example and only mentions the Azure portal as an alternative. There is no equivalent Bash or Azure CLI example for triggering the pipeline, which may disadvantage Linux users. Additionally, Power BI Desktop (a Windows-only tool) is the only visualization tool mentioned, and its steps are detailed without Linux alternatives. PowerShell is presented before the portal method, reinforcing a Windows-first approach.
Recommendations:
- Provide an Azure CLI or Bash example for triggering the Data Factory pipeline, not just PowerShell.
- Mention and, if possible, provide steps for using Power BI on the web or suggest open-source, cross-platform alternatives for data visualization.
- When listing ways to trigger pipelines, present CLI or cross-platform methods before or alongside PowerShell.
- Explicitly state which steps are cross-platform and which are Windows-only, and offer alternatives where possible.
- Consider including a table summarizing which tools/steps are available on Windows, Linux, and macOS.
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Scan History
| Date | Scan ID | Status | Bias Status |
|---|---|---|---|
| 2025-08-17 00:01 | #83 | in_progress | ✅ Clean |
| 2025-07-13 21:37 | #48 | completed | ❌ Biased |
| 2025-07-12 23:44 | #41 | in_progress | ❌ Biased |
| 2025-07-09 13:09 | #3 | cancelled | ✅ Clean |
| 2025-07-08 04:23 | #2 | cancelled | ❌ Biased |
Flagged Code Snippets
1. To view the Data Lake Storage Gen2 account and access key, enter the following command:
To trigger the pipeline, you have two options. You can:
* Trigger the Data Factory pipeline in PowerShell. Replace `RESOURCEGROUP` and `DataFactoryName` with the appropriate values, and then run the following commands:
Re-execute `Get-AzDataFactoryV2PipelineRun` as needed to monitor progress.
Or you can:
* Open the data factory and select **Author & Monitor**. Trigger the `IngestAndTransform` pipeline from the portal. For information on how to trigger pipelines through the portal, see [Create on-demand Apache Hadoop clusters in HDInsight by using Azure Data Factory](hdinsight-hadoop-create-linux-clusters-adf.md#trigger-a-pipeline).
To verify that the pipeline has run, take one of the following steps:
* Go to the **Monitor** section in your data factory through the portal.
* In Azure Storage Explorer, go to your Data Lake Storage Gen2 storage account. Go to the `files` file system, and then go to the `transformed` folder. Check the folder contents to see if the pipeline succeeded.
For other ways to transform data by using HDInsight, see [this article on using Jupyter Notebook](/azure/hdinsight/spark/apache-spark-load-data-run-query).
### Create a table on the Interactive Query cluster to view data on Power BI
1. Copy the `query.hql` file to the LLAP cluster by using the secure copy (SCP) command. Enter the command:
This script creates a managed table on the Interactive Query cluster that you can access from Power BI.
### Create a Power BI dashboard from sales data
1. Open Power BI Desktop.
1. On the menu, go to **Get data** > **More...** > **Azure** > **HDInsight Interactive Query**.
1. Select **Connect**.
1. In the **HDInsight Interactive Query** dialog:
1. In the **Server** text box, enter the name of your LLAP cluster in the format of `https://LLAPCLUSTERNAME.azurehdinsight.net`.
1. In the **database** text box, enter **default**.
1. Select **OK**.
1. In the **AzureHive** dialog:
1. In the **User name** text box, enter **admin**.
1. In the **Password** text box, enter **Thisisapassword1**.
1. Select **Connect**.
1. From **Navigator**, select **sales** or **sales_raw** to preview the data. After the data is loaded, you can experiment with the dashboard that you want to create. To get started with Power BI dashboards, see the following articles:
* [Introduction to dashboards for Power BI designers](/power-bi/service-dashboards)
* [Tutorial: Get started with the Power BI service](/power-bi/service-get-started)
## Clean up resources
If you're not going to continue to use this application, delete all resources so that you aren't charged for them.
1. To remove the resource group, enter the command: