How Do I Ensure Data Flows Properly Between Systems?

Direct Answer

Guarantee healthy data flow by defining a data contract, mapping it across systems, and enforcing change control. Use least-privilege integrations with retry/queueing, dedupe rules, and upsert logic keyed on stable IDs. Add observability—sync success rate, latency, and error catalogs—with alerts and rollback paths. Review mappings monthly and after any schema change to prevent regressions.

Assign a system of record for each object and author a data contract that codifies formats, validations, and enumerations. Choose stable keys and define matching logic for merges to prevent duplication. Create a field-level mapping with explicit transformations and survivorship rules—what wins when systems disagree.

Build integrations with reliability patterns: retries, queueing, and dead-letter handling. Add pre-write validators to block bad data and post-sync checks to reconcile record counts. Operationalize with health dashboards—success %, latency, top errors—and alerts tied to SLAs. Every schema change flows through design review, sandbox testing, release notes, and rollback.

TPG POV: We implement contracts, mappings, and monitoring across Salesforce/HubSpot and adjacent tools—combining change control with governed releases so improvements stick.