Connector Coverage Audit (Onboarding)

Connector Coverage Audit (Onboarding)

1. 01

   Inventory every source system the client uses

   List all SaaS tools, databases, and on-prem systems that generate data the client cares about. Include CRMs, ad platforms, support desks, and any custom internal tools.

2. 02

   Map each source to a target destination

   For each source, define where the data needs to land: a warehouse like BigQuery or Snowflake, or an operational tool like Salesforce or HubSpot. This clarifies whether you need ETL, ELT, or reverse ETL.

3. 03

   Check connector availability across candidate platforms

   Compare the source list against the connector catalogs of platforms like Weld (300+ sources), Dataddo (400+ connectors), and Polytomic. Note any gaps that would require custom development or a workaround.

4. 04

   Assess real-time vs batch requirements

   Determine which data flows need near-real-time sync (e.g., ad spend for live dashboards) versus daily batch. This affects platform choice and pipeline design.

5. 05

   Evaluate transformation needs and tooling

   Check whether the client's team uses dbt or prefers built-in SQL. Platforms like Weld support dbt Cloud and Core, while others may have proprietary transformation layers.

6. 06

   Review data volume and API rate limits

   Estimate row counts and API call frequency to ensure the chosen platform can handle the load without throttling or excessive cost.

7. 07

   Document the final architecture and decision rationale

   Write a short summary of the chosen platform, the connectors used, and any gaps or risks. This becomes the reference for future changes and client communication.