A custom dataset is a blank report that contains metrics and attributes that can be used as a starting point for building a Dynamic or Dossier Dashboard. In certain use cases, it might not be possible to find all necessary data for a given dashboard within the existing cubes and a custom report is necessary.
Note: Please create custom datasets only when necessary. If you are unsure if a custom dataset is required please consult your CSM.
When it has been determined that a custom dataset is necessary, please follow the guidelines below for best results:
- First, check for similar datasets to avoid replications
- Use only certified and necessary attributes and metrics for your analysis
- After creating the report check the SQL for cross joins. If sub-optimal joins are present the system may not execute the report or return an error if it detects a bad query
- Verify data against the source
- Check the size of the report. Custom datasets should be limited to a few thousand rows. If your custom report is larger please consider using an existing cube
- Once the dataset is certified please work with your CSM to migrate it into an iCube
To check the SQL of a report
- Execute the report. While the report is loading click on the option "Show Report Details":
- Under Report Details you will find the SQL statement that contains any bad joins, specifically "Cross Joins." Cross joins can be caused by pulling in only attributes without a metric, neglecting to filter data across tables in any way. Evidence in the SQL statement that a cross join is present can be repeated metrics across rows. Please see the screenshot in below to observe a cross join:
- An alternative way to view the SQL is to execute the report completely and then navigate to the "Tools" drop-down menu
- Select Report Details Page
- Once on the details page, you will see a box labeled "SQL statement."
- Check the SQL for any bad joins
If a bad join is observed or an error is returned while executing the report please contact support@numerify.com to continue troubleshooting.
Related Article: Pros and Cons of Using an iCube vs. a Custom Dataset in Digital.ai Intelligence
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