What data integration covers
Data integration is the umbrella term for moving data between systems. It includes:
- ETL (Extract, Transform, Load) — pull data from a source, reshape it, load into a destination.
- ELT (Extract, Load, Transform) — modern variant where the transform happens in the destination warehouse.
- Reverse ETL — pushing warehouse data back into operational systems (CRM, marketing tools).
- Real-time syncs — change-data-capture patterns keeping two systems aligned continuously.
- API-driven integration — applications calling each other directly, orchestrated by a workflow platform.
Why this is hard at enterprise scale
Every application has its own data model. Salesforce’s “opportunity” doesn’t match NetSuite’s “sales order.” Workday’s “employee” doesn’t map cleanly to a custom internal system’s “user.” Integration isn’t just moving bytes — it’s translating between those models reliably, dealing with failures gracefully, and doing it consistently as the models change over time.
Doing this ad-hoc (one script per integration) works until it doesn’t. Then you end up with a graveyard of brittle scripts that break when anyone changes anything.
How Tray.ai handles it
Intelligent iPaaS is Tray.ai’s integration pillar. It combines:
- A 700+ connector library so most data paths are pre-built.
- Visual workflows so complex integration logic is readable and maintainable, not script-only.
- Data Engineering (SQL Transformer, VectorTables) for in-flight transformation.
- Governed execution — retry policies, error handling, audit trails, observability.
The modern shift
Traditional iPaaS was built for data integration as the primary job. Modern orchestration (see AI-native) treats data integration as one job among several — alongside process automation, AI agent deployment, and MCP governance.
Done right, the same workflows that integrate data can also expose that data to AI agents via Agent Gateway. That coherence is what customers like IBM get out of the platform — 9M+ records moved in 5 minutes a day, using the same Tray.ai infrastructure that handles their other workflow work.