Insurance · change data capture
Implementing CDC for near-real-time data ingestion
Established full-load and incremental data flows from legacy systems, with data-quality remediation, testing, monitoring, and production support.
Delivered engagementThe challenge
An insurance organisation needed near-real-time ingestion from established Oracle and DB400 systems while retaining a controlled initial load and reliable incremental processing.
Legacy data quality issues, inconsistent source records, and the need for coordinated SIT and UAT made replication configuration alone insufficient.
What Monic delivered
Monic designed the full-load and delta-load data flows, installed and configured Informatica PowerExchange for change data capture, and implemented approaches for identifying and correcting problematic legacy data.
The team coordinated testing with business and technical stakeholders, resolved source-data discrepancies, monitored CDC processes in production, and supported performance and error-handling improvements.
The result
The engagement established the CDC flows and production-support practices needed for near-real-time insurance data ingestion, covering both initial loading and ongoing incremental change processing.
What this case demonstrates
The engineering lessons behind the result.
These are the delivery patterns a team facing a similar operating problem should plan for.
CDC includes an initial-load strategy
The transition from a controlled full load into incremental capture must preserve completeness and define how gaps, duplicates, ordering, and restarts are handled.
Legacy quality affects real-time flow
Faster ingestion does not correct inconsistent source records. Detection, remediation, and business review still need to be part of the solution.
Production monitoring completes the design
Latency, errors, stopped capture, source changes, and reconciliation exceptions need observable signals and a support owner who can respond.