FIRST-PARTY DATA / DATABRICKS + WHITEBOXX AI
Compare the cohorts
you measure in Databricks.
Use prepared cohort aggregates in a business review, with group sizes and definitions alongside the results.
THE ANALYTICAL TASK
How do the cohorts differ?
Your team may already maintain cohort measures but need to explain how the groups compare. Start with the prepared table and its definitions.
Select the SQL warehouse, catalog, schema and table. The existing query groups the configured cohort field and returns reach, average overlap and spend measures. We map those fields to your prepared data.
THE OUTPUT
A cohort comparison with the definitions attached.
The report compares the returned measures and identifies questions to investigate. Analysing a trend also requires comparable historical inputs.
INPUTS AND DEFINITIONS
Choose the cohorts and measures to compare.
| Input or measure | What to establish |
|---|---|
| Cohort membership | Document how each group is constructed. |
| Numeric fields | Confirm the meaning of overlap and spend in your table. |
| Historical comparison | Supply comparable periods before interpreting movement. |
CONNECTOR BUILDING BLOCKS
Configure the SQL warehouse connection.
Existing code submits aggregate statements through the Databricks SQL Statements endpoint and maps the columns into evidence records. We verify execution status, field mappings and result completeness.
This approach queries a SQL warehouse. Delta Sharing and Databricks Clean Rooms require separate connections. The comparison must reconcile with your approved table.
PILOT ACCEPTANCE
How should you evaluate a Databricks integration?
| Check | Evidence to review |
|---|---|
| Confirm the cohort table | Reconcile the selected cohort field, reach, overlap and spend columns with the prepared SQL warehouse table. Retain the definitions alongside the comparison. |
| Check statement completion | Verify that the returned statement completed and that all required result rows were retrieved before presenting cohort differences. |
| Separate a snapshot from a trend | Describe one-period differences as a comparison. Add comparable historical tables before calculating change or suggesting a cohort trend. |
PLANNING THE IMPLEMENTATION
Is this a ready-to-use Databricks connection?
Whiteboxx has connector building blocks for Databricks, which must be configured and validated for the selected tenant, source objects and analytical task. The project still needs result reconciliation and any additional application, historical-data or delivery work described above.
Use the pilot evaluation guide