Project Overview
Implementation of CDC and Data Stream. We assisted BNI in establishing a robust data ingestion architecture to capture and propagate core banking data changes into a unified foundation.
Implementation of CDC and Data Stream. We assisted BNI in establishing a robust data ingestion architecture to capture and propagate core banking data changes into a unified foundation.
The Challenge
The bank faced rapid data growth and fragmented legacy pipelines that were difficult to monitor and tightly coupled to core systems, increasing operational risk.
The bank faced rapid data growth and fragmented legacy pipelines that were difficult to monitor and tightly coupled to core systems, increasing operational risk.
The Solution
We implemented standardized CDC-driven pipelines with centralized orchestration and enterprise-grade governance to meet rigorous banking regulatory and audit requirements.
We implemented standardized CDC-driven pipelines with centralized orchestration and enterprise-grade governance to meet rigorous banking regulatory and audit requirements.
The Result
The project delivered reliable, near-real-time data availability for reporting and analytics while reducing the processing load on core transactional systems through efficient offloading.
The project delivered reliable, near-real-time data availability for reporting and analytics while reducing the processing load on core transactional systems through efficient offloading.
About
Bank Negara Indonesia (BNI) is one of Indonesia’s largest state-owned financial institutions, dedicated to providing integrated digital-based financial solutions with a focus on both corporate and consumer banking excellence.
The Business Challenges
- Rapid growth of transactional and master data across core banking systems (LOAN, INV) requiring scalable ODS and ODW integration.
Need for CDC-based near-real-time data synchronization to support operational reporting and historical analytics.
Existing pipelines were fragmented, difficult to monitor, and tightly coupled to core systems, increasing operational risk.
Sibernetik Solutions
Implemented a CDC-driven data ingestion architecture to capture and propagate data changes from core banking systems into ODS and ODW layers.
Established a unified data foundation with clearly defined ODS, ODW, and historical layers supported by consistent data modeling.
Standardized data pipelines to support both near-real-time and batch processing with centralized orchestration and monitoring.
Applied enterprise-grade governance, monitoring, and operational controls to meet banking regulatory and audit requirements.
The Business Benefits
- Reliable and timely availability of operational and historical data for reporting, analytics, and downstream consumption.
- Reduced load and dependency on core transactional systems through CDC-based offloading.
- Improved pipeline stability, observability, and operational control across data ingestion and transformation processes.
- Faster and more consistent data delivery to support business reporting, analytics, and future AI initiative.
