Azure DevOps
Power BI is an extremely powerful tool that allows users to create stunning visuals and reports with ease. One of the key features of Power BI is the ability to connect to multiple data sources, including Azure DevOps, a cloud-based service for managing software development projects.
In this article, we will explore how to use Power Query M Language code to connect to the Azure DevOps data source from inside Power BI. We will cover the steps required to establish the connection, query the data, and transform it to create meaningful reports and visuals.
Step 1: Establishing the Connection
The first step in connecting to the Azure DevOps data source is to establish a connection in Power BI. To do this, we will need to use the “Azure DevOps” connector in Power BI. Here are the steps to follow:
1. Open Power BI and click on the “Get Data” button on the Home tab.
2. In the “Get Data” window, select “Azure DevOps” from the list of available connectors.
3. Enter the URL of your Azure DevOps account and click “OK”.
4. In the “Connect to Azure DevOps” window, enter your credentials and click “Connect”.
Once you have established a connection to the Azure DevOps data source, you can begin to query the data.
Step 2: Querying the Data
After establishing the connection, we can use the Power Query Editor in Power BI to query the data from Azure DevOps. The Power Query Editor provides a user-friendly interface to filter, sort, and transform the data to create meaningful reports and visuals.
To query the data from Azure DevOps, follow these steps:
1. In Power BI, click on the “Transform Data” button on the Home tab.
2. In the Power Query Editor, click on the “Azure DevOps” query in the Queries pane.
3. In the “Query Settings” pane, click on the “Edit Credentials” button to enter your credentials again.
4. Once you have entered your credentials, click on the “Load” button to load the data into the Power Query Editor.
Now that we have loaded the data into the Power Query Editor, we can begin to transform it to create meaningful reports and visuals.
Step 3: Transforming the Data
The Power Query Editor provides a wide range of transformation options to clean, reshape, and combine data from multiple sources. Here are some of the key transformation options you can use to transform the data from Azure DevOps:
1. Filter: Use the filter option to remove unwanted rows or columns from the data.
2. Sort: Use the sort option to sort the data by one or more columns.
3. Group By: Use the group by option to aggregate data by one or more columns.
4. Pivot: Use the pivot option to transpose rows into columns and columns into rows.
5. Merge: Use the merge option to combine data from multiple sources into a single table.
By using these transformation options, you can create meaningful reports and visuals that provide insights into your software development projects.
Step 4: Creating Reports and Visuals
After transforming the data, we can create reports and visuals in Power BI. Power BI provides a wide range of visualization options, including charts, tables, and maps.
To create a report or visual in Power BI, follow these steps:
1. Click on the “Reports” button on the left-hand pane in Power BI.
2. Click on the “New Page” button to create a new report page.
3. Drag and drop the fields from the “Fields” pane onto the report canvas to create visuals.
4. Use the formatting options to customize the visuals and create a polished report.
In summary, using Power Query M Language code to connect to the Azure DevOps data source from inside Power BI provides a powerful way to create meaningful reports and visuals that provide insights into your software development projects. By following the steps outlined in this article, you can establish a connection, query the data, transform it, and create stunning reports and visuals.
