After successfully creating a Transformation based on a template configuration, you will have a list of variables and Operations with all the necessary settings. Now, you need to customize a few parameters to ensure that each SQL request runs successfully. In this article, we will describe the general steps to configure any Transformation template.
Step 1. Replace the 'YOUR_VALUE' text in the variables
As the Transformation template is designed for multiple copies and reuse, it contains a list of variables. Some of these variables already have values that do not need to be changed.
However, in each template, there will be one or more variables to which you need to manually add your custom values. These variables are highlighted with a red background and have a value of "YOUR_VALUE".
For example, each template has variables to indicate the GCP project ID. Note that the accuracy of the dataset path on the 'Used datasets' tab depends on the value of this variable.
You can find the full list of variables for each template in the "Templates gallery" section.
Step 2. Enable or disable Operations that you need
Some templates are so versatile that before running the Transformation, you need to review the list of Operations and disable some of them if you don't have the required BigQuery tables for the SQL query.
For instance, the "Blended Adspend + GA4 Cost Data Import" template has 12 Operations, including data processing from advertising services (Facebook, Twitter, LinkedIn, Criteo, Bing, etc.). If you don't have ad costs in services like Criteo and Bing, you can simply disable these Operations to prevent them from executing during the Transformation run. Read more about this in the article.
Step 3. Share access to used datasets
On the Used datasets tab, you can see a list of datasets specified in the SQL queries of this Transformation. If the service account OWOX BI doesn't have access to a dataset, you will see a red text saying "No access."
Check the GCP project ID and Dataset ID. If you see here the text 'YOUR_VALUE', then go to step 1 and update variables with correct names.
If the GCP Project ID and Dataset ID are correct, click the "Share dataset" button to grant access to this dataset. Please note that only users with BigQuery Admin or BigQuery Data Owner privileges can provide access. Read more about this in the article.
By following these three simple steps, you can easily customize any Transformation template according to your specific needs and ensure the successful execution of your requests. If you have any questions or need further assistance, don't hesitate to reach out to our support team. Happy transforming!