Connect everything. Unify your data ecosystem.

ETL (Extract, Transform, Load) transforms data before loading into the destination — ideal when you need to clean and structure data upfront. ELT (Extract, Load, Transform) loads raw data first, then transforms it in the destination — better for cloud data warehouses with powerful processing. Real-time integration streams data continuously as events occur — essential when you need immediate data availability for operational use cases.

We implement multiple layers of data quality: validation rules at ingestion, transformation logic for standardization, automated testing for schema changes, monitoring for anomalies, and data profiling to catch issues early. We also establish data contracts between systems and implement circuit breakers to prevent bad data from propagating downstream.

Yes, we have extensive experience integrating with legacy systems including mainframes, AS/400, and custom on-premise applications. We use techniques like file-based integration, database replication, screen scraping when necessary, and API wrapping to expose legacy data and functionality to modern systems without disrupting core operations.

Security is built into every integration: encrypted connections (TLS 1.3), OAuth 2.0/SAML for authentication, role-based access controls, data masking for sensitive fields, and comprehensive audit logging. We design for compliance with GDPR, HIPAA, SOC 2, and industry-specific regulations, implementing data residency controls and retention policies as needed.

We design integrations to be resilient to change: schema evolution support, version-aware APIs, automated schema drift detection, and alerting when breaking changes are detected. We also implement transformation layers that isolate downstream systems from upstream changes, giving you time to adapt without breaking existing functionality.