Data Integration

Production-hardened pipelines that feed Reltio and distribute golden records

Typical duration
6–12 weeks
Best fit
Organizations connecting five or more source systems to Reltio
Deliverables
6 included
Engagement
Fixed scope

Overview

Integrations fail quietly — and by the time someone notices, months of bad data have already propagated. We design pipelines that anticipate failure: idempotent loads, dead-letter queues, automatic retries, and monitoring that alerts before the business feels the impact. Whether you're on Informatica IICS, MuleSoft, or custom Python, we've built it against dozens of source system combinations.

What's included

Source system profiling and connectivity mapping
Real-time and batch pipeline architecture and build
Snowflake, Databricks, and cloud warehouse integration
SAP, Salesforce, and Workday connector patterns
Error handling, dead-letter queues, and retry logic
Pipeline monitoring dashboards and operational runbooks

Designed for the production edge cases that break generic pipelines

Integration failures are where MDM implementations go wrong after go-live. A pipeline that works in testing breaks at production volume, or when a source system sends an unexpected null, or when a batch job overlaps with a real-time feed. We design for failure modes first.

Our integration patterns come from experience across Informatica IICS, MuleSoft, and custom Python implementations — with production-hardened error handling, dead-letter queues, and alerting built in from day one, not bolted on after the first outage.

Engagement details

Typical duration
6–12 weeks
Best for
Organizations connecting five or more source systems to Reltio