Seamless Core System Migration: The Move of Large-Scale Banking and Insurance ERP Data to a Modern Cloud Architecture
⛅ Did you know that core system migrations in large financial institutions, which typically rely on manual data mapping and validation, often require parallel runs lasting over 18 months?
The Core Challenge
The migration of multi-terabyte ERP and core policy/banking system data from on-premise infrastructure to a contemporary cloud architecture is a monumental undertaking for finance and insurance firms. This is far more than a simple ‘lift and shift’; it necessitates the precise, governed transformation and synchronisation of mission-critical data, impacting everything from customer ledgers to regulatory reporting. For data professionals, the task is balancing speed and agility against the absolute requirement for data parity and zero production downtime.
The Inertia of Legacy Systems
Legacy systems in banking and insurance are inherently monolithic, often built upon decades of bespoke code and complex data structures. The primary issue facing data engineers is the immense risk linked to the cutover phase.
Traditional migration methods necessitate prolonged system freezes or “big bang” deployments, creating unacceptable operational risk and service disruption.
Furthermore, maintaining continuous regulatory compliance and data lineage throughout the transition demands excessive manual coding, meticulous error handling, and lengthy validation cycles that drain resources and inflate project costs considerably.
IOblend’s Blueprint for Seamless Transition
IOblend offers a paradigm shift in core system migration by fundamentally de-risking the transition. Key solutions for data experts include:
- Real-Time Data Synchronisation: IOblend utilises Change Data Capture (CDC) to enable continuous, real-time synchronisation between the legacy ERP and the new cloud environment. This facilitates risk-free parallel runs, where both systems operate simultaneously whilst validation is performed, eliminating service disruption during the final cutover.
- Automated DataOps & Governance: Every pipeline automatically embeds technical governance features, including record-level lineage, schema management, and automated data quality checks. This capability ensures complete data trust and facilitates stringent audit trails, meeting the stringent regulatory demands of the financial sector.
- Scale and Performance: Designed for banking and insurance volumes, the IOblend Engine handles both streaming and batch data via Kappa architecture, enabling massively parallel processing capable of executing complex transformations such as calculating adjusted policy values or running real-time risk models at speeds exceeding ten million transactions per second.
Unlock your data’s potential and minimise transition risk with IOblend.
IOblend presents a ground-breaking approach to IoT and data integration, revolutionizing the way businesses handle their data. It’s an all-in-one data integration accelerator, boasting real-time, production-grade, managed Apache Spark™ data pipelines that can be set up in mere minutes. This facilitates a massive acceleration in data migration projects, whether from on-prem to cloud or between clouds, thanks to its low code/no code development and automated data management and governance.
IOblend also simplifies the integration of streaming and batch data through Kappa architecture, significantly boosting the efficiency of operational analytics and MLOps. Its system enables the robust and cost-effective delivery of both centralized and federated data architectures, with low latency and massively parallelized data processing, capable of handling over 10 million transactions per second. Additionally, IOblend integrates seamlessly with leading cloud services like Snowflake and Microsoft Azure, underscoring its versatility and broad applicability in various data environments.
At its core, IOblend is an end-to-end enterprise data integration solution built with DataOps capability. It stands out as a versatile ETL product for building and managing data estates with high-grade data flows. The platform powers operational analytics and AI initiatives, drastically reducing the costs and development efforts associated with data projects and data science ventures. It’s engineered to connect to any source, perform in-memory transformations of streaming and batch data, and direct the results to any destination with minimal effort.
IOblend’s use cases are diverse and impactful. It streams live data from factories to automated forecasting models and channels data from IoT sensors to real-time monitoring applications, enabling automated decision-making based on live inputs and historical statistics. Additionally, it handles the movement of production-grade streaming and batch data to and from cloud data warehouses and lakes, powers data exchanges, and feeds applications with data that adheres to complex business rules and governance policies.
The platform comprises two core components: the IOblend Designer and the IOblend Engine. The IOblend Designer is a desktop GUI used for designing, building, and testing data pipeline DAGs, producing metadata that describes the data pipelines. The IOblend Engine, the heart of the system, converts this metadata into Spark streaming jobs executed on any Spark cluster. Available in Developer and Enterprise suites, IOblend supports both local and remote engine operations, catering to a wide range of development and operational needs. It also facilitates collaborative development and pipeline versioning, making it a robust tool for modern data management and analytics
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