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Asked: September 27, 20242024-09-27T08:42:21+05:30 2024-09-27T08:42:21+05:30In: SQL

how to connect mysql workbench to power bi

anonymous user

I’m trying to connect MySQL Workbench to Power BI, but I’m running into some difficulties. I have MySQL Workbench running and can access my database without any issues. However, when I attempt to connect it to Power BI, I’m unsure of the correct steps to take. I’ve already installed the MySQL ODBC driver, but I’m not entirely sure how to configure it properly to make the connection work.

In Power BI, I am looking for the right data source option to select, and I’m unsure whether I should be using the MySQL database connector or the ODBC option since I have the driver installed. I’ve tried both methods, but I seem to hit a roadblock at the authentication step; it keeps giving me an error about not being able to reach the database.

Is there a specific way to format the connection string or settings in Power BI that I should be aware of? Any guidance on the steps I need to follow or resources that could help would be greatly appreciated. I just want to be able to visualize my MySQL data in Power BI effectively!

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    1. anonymous user
      2024-09-27T08:42:22+05:30Added an answer on September 27, 2024 at 8:42 am

      Connecting MySQL Workbench to Power BI

      So, you want to connect MySQL Workbench to Power BI? No worries, I’ve got your back! It’s not super hard, but it might feel a bit tricky if you’re new to this. Here’s a simple step-by-step:

      Step 1: Install MySQL ODBC Driver

      First, you need to get MySQL ODBC driver. This helps Power BI talk to your MySQL database.

      • Go to the MySQL Connector/ODBC page.
      • Download the driver that matches your system (32-bit or 64-bit).
      • Install it. Just follow the installation wizard; it’s pretty straightforward!

      Step 2: Create a DSN

      Next up, you need to set up a Data Source Name (DSN) so Power BI knows where to find your MySQL database.

      1. Search for “ODBC Data Sources” in your Windows search.
      2. Open it up (choose 32-bit or 64-bit based on your driver).
      3. Click on the System DSN tab and hit Add.
      4. Select the MySQL ODBC driver you just installed and click Finish.
      5. Fill in the details like the DSN name, server, user, and password. Test the connection to make sure it works!

      Step 3: Connect Power BI to MySQL

      Now it’s time to open Power BI and link it to your fancy MySQL database!

      1. In Power BI, go to Get Data.
      2. Select ODBC.
      3. Pick your DSN from the list and click OK.
      4. Input your MySQL credentials again if needed, and hit Connect.

      Step 4: Start Analyzing!

      If all went well, you should see your MySQL tables now! You can pick which data to load and start creating your reports and visuals.

      But remember, if it doesn’t work the first time, don’t panic! Double-check your connection details and try again. Happy analyzing!

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    2. anonymous user
      2024-09-27T08:42:23+05:30Added an answer on September 27, 2024 at 8:42 am


      To connect MySQL Workbench to Power BI, you first need to ensure that you have the necessary ODBC driver installed. Go to the MySQL official website and download the MySQL ODBC Connector for the version of MySQL you are using. Once installed, open the ODBC Data Source Administrator and create a new Data Source Name (DSN) by selecting the MySQL ODBC driver. Provide the required connection details, such as the server address, port, database name, user ID, and password. Test the connection to ensure it’s successful before proceeding.

      After confirming the ODBC connection, open Power BI Desktop. Go to the “Get Data” option and select “More.” In the Get Data window, navigate to the “Other” category and select “ODBC.” Choose the DSN you created for your MySQL database from the dropdown menu. After connecting, you’ll be able to select tables or views to import into Power BI for visualization. Remember that after importing the data, you can leverage Power BI’s data modeling features to create relationships, calculated columns, and measures based on the imported data, facilitating a robust analytics experience.

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