Power BI

Power BI is a business analytics service by Microsoft that provides interactive visualizations and business intelligence capabilities, with an interface simple enough for end users to create their own reports and dashboards.

Using Weld to build a data destination ensures that all your company's systems data is centralized, transformed, and ready for analysis within PowerBI.

How to connect to Weld

Connect your data in Weld to Power BI through a direct connection between your destination and Power BI.

Connect BigQuery

Connecting Power BI to Google BigQuery is a relatively straightforward process.

Here are the steps:

You'll need a Google account or a Google service account to sign in to Google BigQuery.

  1. Launch Power BI Desktop: Start the application on your computer.
  2. Get Data: On the Home tab, click on Get Data in the toolbar.
  3. Select More...: In the menu that appears, select More... to view all data connectors.
  4. Search for BigQuery: In the Get Data window, use the search bar to find BigQuery and then select Google BigQuery from the list of options. Click Connect.
  5. Sign in to Google Account: In the Google BigQuery window that appears, you'll need to sign in to your Google account that has access to the BigQuery data. Click Sign in and follow the prompts.
  6. Allow permissions: Google will ask for some permissions to let Power BI access your Google account. Read the permissions carefully and, if you agree, click Allow.
  7. Choose the Project and Dataset: After successfully signing in, select the Project and Dataset from your Google BigQuery account.
  8. Load or Edit Data: Choose whether to load the data into Power BI or edit the data before loading. Click Load to load the data directly, or click Edit to launch the Power Query Editor where you can transform the data before loading it.
  9. Navigate the Data: Now your data is loaded into Power BI and you can start building your reports.

Remember that while BigQuery does not charge for the data itself, it does charge for querying data. Each query from Power BI may incur costs, so creating views in BigQuery for commonly used data is recommended to reduce costs.

For more details please consult the Microsoft Power BI to BigQuery page: https://learn.microsoft.com/en-us/power-query/connectors/google-bigquery

Connect BigQuery (Service Account)

You can also choose to use a Service Account to connect BigQuery in PowerBI. Using a service account for authentication provides enhanced security and automation capabilities, eliminating the need for manual user intervention and frequent re-authentication that comes with OAuth.

To connect a using a Service Account, ensure you have your service account JSON file ready.

  1. Open PowerBI Desktop: Launch the PowerBI Desktop application on your computer.
  2. Get Data: On the Home ribbon, click on Get Data.
  3. Select Google BigQuery: In the Get Data window, search for Google BigQuery. Click on it and then hit the Connect button.
  4. Enter Project ID: A prompt will appear asking for your Google BigQuery project ID, which can be found in your Google Cloud Console.
  5. Choose Authentication Method: You'll be prompted to authenticate. Select the Service Account option from the list.
  6. Upload JSON Key: An option labeled Key File will appear. Click on it, navigate to your service account JSON file's location, and upload it.
  7. Initiate Connection: With the JSON file uploaded, click the Connect button to establish a connection with your Google BigQuery dataset.
  8. Select Dataset: Once connected, choose the desired dataset or table you wish to import to PowerBI from the displayed list.
  9. Load Data: Highlight your chosen dataset or table and click on the Load button to import the data into PowerBI.

Connect Snowflake

Connecting Power BI to Snowflake is also quite straightforward.

Here are the steps:

  1. Launch Power BI Desktop: Start the Power BI Desktop application on your computer.

  2. Get Data: On the Home tab in the toolbar, click on Get Data.

  3. Select Database: In the menu that appears, select Database from the categories on the left, then select Snowflake from the list of options. Click Connect.

  4. Enter Snowflake Details: In the Snowflake window that appears, you'll need to enter your Snowflake server details. Enter the server name, database name, and, optionally, the warehouse, role, and schema.

    The server name should follow this format: [account_name].[region_id].snowflakecomputing.com

  5. Choose Connection Method: Choose how you want to connect to the Snowflake data. You can select Import to import the data into Power BI, or DirectQuery to leave the data in Snowflake and query it directly from Power BI.

  6. Enter Credentials: After clicking Connect, you'll be prompted to enter your Snowflake credentials. Choose Database from the left, then enter your Snowflake username and password. Click Connect again.

  7. Select Tables: You'll now see a Navigator window where you can select the tables or views you want to load into Power BI. Select the ones you need and click Load to load the data directly, or Edit to launch the Power Query Editor where you can transform the data before loading it.

  8. Navigate the Data: Your data from Snowflake is now loaded into Power BI and you can begin building your reports.

Remember to always handle your data responsibly and be aware that depending on your Snowflake plan, querying large volumes of data frequently can incur additional costs.

For more details please consult the Microsoft Power BI to Snowflake page:

https://learn.microsoft.com/en-us/power-bi/connect-data/service-connect-snowflake

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