Data Integration Services

ETL transforms data before loading it into the target, which suited older, compute-constrained warehouses. ELT loads raw data first and transforms it inside a modern warehouse or lakehouse, which is more flexible and easier to test. Change data capture is a way of extracting data: it reads database transaction logs to capture each insert, update and delete as it happens, enabling low-latency replication with little impact on source systems.

For popular SaaS applications and databases, managed connectors usually save significant engineering time and handle API changes for you. Custom pipelines make sense for niche or internal systems, very high volumes where connector pricing becomes expensive, or when you need special handling. Most clients use a mix, and we compare total cost, including maintenance, for each source.

Match latency to the decision being made. Daily or hourly batch is enough for most reporting and is cheaper to run. Minutes matter for inventory, order status and customer service. Seconds matter for fraud detection, personalization or operational alerts. We define freshness requirements per flow, and design only the flows that truly need it as streaming.

We combine prevention and detection. Data contracts agreed with source owners define expected fields and types. Pipelines detect new, removed or changed columns automatically, handle compatible changes without failing, and alert owners about breaking ones. For event streams, a schema registry enforces compatibility rules, so producers cannot publish changes that break consumers.

Cost depends on the number of systems and flows, required latency, data volumes, availability of connectors, transformation complexity and monitoring needs. Tool licensing and cloud consumption add running costs. After mapping your landscape we provide an estimate per phase, and we often start with the highest-value flows so benefits appear before the full scope is complete.

All connections use encryption in transit, credentials are stored in a secrets manager rather than in code, and integration services run with least-privilege accounts. Private networking is used where supported. Sensitive fields can be masked or excluded at extraction. Every flow is logged, and we document data movement so security and privacy teams can approve it.