Create a Datamart
This guide provides a straightforward process for creating a datamart in Databrain, allowing users to efficiently manage and analyze data.
Last updated
This guide provides a straightforward process for creating a datamart in Databrain, allowing users to efficiently manage and analyze data.
Last updated
What is a Datamart?
A datamart is a specialized subset of a data warehouse designed to cater to the analytical needs of a specific department. It allows users to efficiently manage and analyze relevant data by providing a more focused and optimized dataset.
Purpose of Datamart
A datamart solves the problem of managing large and complex datasets by delivering fast query performance and simplified access to data, tailored to the needs of specific departments.
Initial Access:
In the "Data Studio" page of Databrain, navigate to the "Datamarts" section.
Click on "+ Data Mart" button in the top right corner.
Configure Datamart:
Enter a suitable name for your datamart and choose the corresponding datasource from the dropdown list.
Check "Enable Database Tenancy" (optional) and click on "Next".
Database tenancy refers to organizing and controlling access to data based on specific groups. It ensures that each group can access only their own data, keeping it secure and separate from other.
Select Tables:
Use the search box to find specific tables or browse available tables in the schema.
Select required tables and click "Next".
Configure Columns:
For each column, you can configure:
ALIAS: Create custom names for columns
HIDE TO: Set visibility options
TRANSFORM: Apply data transformations
Then, click "Next".
Configure Tenancy:
Set "Tenancy Level" as table or database.
If tenancy level is table, then select the table containing customer information from the dropdown list.
Choose "Primary Key" for customer identification and select "Customer Name" column.
Finally, click "Complete" to finish the datamart creation.
For a detailed guide to create the semantic layer for the datamart, kindly refer the following link:
