This article explains what tables and table groups are in data warehousing and data lake destinations. Note that tables and table groups were previously called queries and schemas.
A table group, previously known as a schema, is a collection of tables that define how data is transferred from a data source to a data warehouse or a data lake destination. Each table represents a specific set of fields from the data source and corresponds to a table or file in the destination, depending on whether it's a data warehouse or data lake. The table names will be the names of the tables/files created or updated during the transfer.
In data warehouse and data lake transfers, a table defines the fields pulled from the source. Filters, options, date ranges, and accounts selected when creating the table don't affect the transfer results.
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.
Benefits of table groups
One of the benefits of table groups is their versatility in transferring data to multiple destinations. For example, an agency user might create a table group that they use for all their clients. They can build their custom table group in the Table Manager once and use the same table group and tables in all their transfers.
Different table group types
Premade table groups
Each data source connector comes with one or more premade table groups that can be used in data warehousing and data lake destinations. These premade table groups are created by Supermetrics and provide commonly used fields for each data source. They aim to be as broadly useful as possible for everyone. The default paid license includes access to the premade table groups.
Supermetrics premade table groups adhere to the following principles:
- Comprehensive: The table groups include a wide range of metrics and dimensions to enable users to answer various business questions using the premade tables.
- Denormalized tables: Each table group aims to create multiple tables per data source in a customer's dataset, making it easier to connect to tools like Google's Looker Studio and analyze the data. Data is stored in a denormalized format to include as many compatible metrics and dimensions in a single table as possible.
- Normalized common metrics and dimensions: Standardizing naming conventions among data sources is a goal of the premade table groups.
- Clear table names: Target field names for premade table groups improve readability and usability.
- Backward compatibility: Supermetrics is committed to maintaining the form and structure of the premade table groups to ensure backward compatibility as much as possible.
Note
Using a premade table group may lead to discrepancies when comparing data at different levels. You can solve this issue by using a custom table group that includes only dimensions to compare data at the same level as the native data source UI.
Custom table groups
Custom table groups are created by users based on their preferences, offering the flexibility to include a combination of fields that best suits their needs and use cases. Custom table groups are usually lighter to run compared to premade table groups, as they typically include fewer fields.
You can select your desired fields in the Table Manager to create custom table groups and use them in transfers. The same custom tables can be used as queries in the API and Power BI products. Learn how to set up custom table groups.
If you have any questions about tables and table groups, reach out to our support team.