Warehouse Readiness Review (Onboarding)

Warehouse Readiness Review (Onboarding)

1. 01

   Confirm the client's warehouse destination and access level

   Verify whether the target is BigQuery, Snowflake, Redshift, or another warehouse, and confirm the integration platform has a maintained connector for it. Check read and write permissions before any pipeline is built.

2. 02

   Inventory the source systems the client actually uses

   List every SaaS app, database, and on-prem system that holds data the client needs. Compare this list against the connector catalogs of candidate platforms, noting any gaps that would require custom work.

3. 03

   Assess data volume and sync frequency requirements

   Estimate row counts and change rates for each source to determine whether full, incremental, or CDC replication is appropriate. This shapes cost and latency expectations for the client.

4. 04

   Review existing data models and transformation logic

   Check whether the client already uses dbt or SQL transformations that need to be preserved. Confirm the platform supports the same transformation workflow, whether through dbt Cloud, dbt Core, or a built-in SQL workspace.

5. 05

   Document any reverse ETL destinations and their update patterns

   Identify which operational tools, such as Salesforce or HubSpot, will receive processed data. Note whether updates should be full refreshes or incremental, and whether bidirectional sync is required.

6. 06

   Define data quality and error-handling expectations

   Agree on what happens when a sync fails or a schema changes. Establish alerting thresholds and a rollback plan so the client knows how pipeline issues will be surfaced and resolved.

7. 07

   Create a reusable pipeline template for future clients

   Once the first pipeline is validated, abstract the configuration into a template that can be duplicated for similar client stacks. This reduces setup time on the next engagement and builds a repeatable delivery asset.