Custom table groups, formerly called custom schemas, allow you to pick the exact fields you're interested in transferring to your data warehouse or data lake.
Custom table groups are data source-specific. A table group created for one data source won't be displayed when creating transfers for other data sources.
The saved tables can also be used as queries in other Supermetrics destinations. Note that when using the tables as API queries in the Supermetrics API product, the accounts, filters, and options that were selected when saving the table affect the query results.
- Log in to the Supermetrics Hub.
- In the sidebar, click Storage → Table Manager.
- Select the data source you want to create the table group for.
- In the table list view, click New Table Group to create a new table group. Note that Table groups were formerly called Schemas.
- Give a name for your table group to easily identify it.
- Once the table group is created, click Add table to create a new table for the table group. Tables define a set of fields you want to write to your data warehouse. Note that Tables were formerly called Queries.
- Select the relevant fields to include in the tables (formerly queries). You can choose from premade tables or create custom tables.
- To preview the data, you can select filters, options, date ranges, and accounts. However, these settings won't affect your data warehouse transfers. The same table groups can be used in multiple transfers, each pulling data for separate date ranges and ad accounts.
- Click Save to add the table to the table group.
To add more tables to the group, repeat steps 6-9.
When creating a data transfer, you can select the custom table group you want to transfer to your data warehouse. This allows you to easily manage and transfer the precise sets of data that you require.
You can also use Query Manager to create Custom table groups. The Query Manager still uses the old terminology — Queries for Tables, and Schemas for Table groups.
- Log in to the Supermetrics Hub.
- In the sidebar, click API.
- Select for Data Warehousing from the dropdown menu next to the page title.
- Select the data source you want to create the schema for.
- Open the Query tab.
- Select the metrics and dimensions to use for your query.
- You can use queries from pre-built schemas as a template. In the Schemas tab, click a query under any default schema — this will take you back to the Query tab and fill the selected query into the configuration, where you can continue to modify it.
- Set Select dates as a 1-day range, preferably yesterday. A single account should be sufficient for your data preview.
- Include the Date dimension in your query to load your data incrementally, day by day. If the date isn't included, we'll snapshot all available history, overwriting each day.
- Click Run to validate the query.
- Click Save as to save the query and add it to a schema.
- Give a name for the query.
- Give a name for your new schema (or if you have already created schemas, select a schema from the dropdown menu).
- Click OK.
You can add multiple queries to one schema by repeating steps 5-9. Each query corresponds to one table or file type in your data destination.
When you're ready with your custom schema, you can use it in your data transfers to BigQuery and other data warehouse and cloud storage destinations. To repurpose the saved query setup in the Query Manager, access it in the Schemas tab.