A leading multinational banking and financial services corporation in Asia
Data Governance, Metadata management, System Integration, Business Glossary, Data Dictionary, Big Data Governance, BCBS 239 Compliance.
The client wanted to build a data-driven culture within the organization by investing in strategic data initiatives, of which a key element was a modern data platform. To enable a future-proof data platform, the client needed to manage all the legacy systems where the technical, business and operational metadata was stored. This metadata was scattered, unorganized and poorly managed. Some efforts had been made in the past using Excel sheets to manage this metadata but the information was often out of date and incomplete and had no real ownership. The most prominent challenges discovered were:
- What are the data management standards for different business units?
- What types of data are available within the databases that stored their information?
- Where are the reports stored and what data does it consume?
- Who ultimately owns the data across the data pipeline?
- How is the data linked with each other?
- Do we enough information to perform impact analysis for incident management?
Our RXP Insights consultants planned, developed, and implemented a data governance and metadata management solution, leveraging the agile framework. Collibra was chosen as a strategic tool integrated with the modern data platform for the data challenges and BCBS 239 compliance requirements. Our consultants helped the client ascertain their existing enterprise data governance maturity level, their legacy systems’ readiness, and performed a high level gap analysis on prerequisites for a successful implementation. Collibra was designed, configured, customized and deployed to meet the use cases and agreed operational model. Our consultants also designed, planned, and implemented a migration solution for existing metadata and integration to the Collibra solution.
The Outcome & Benefits
End-users can leverage a centralized business glossary and data dictionary to understand the context of the business data, technical data and operational data when they are consuming data, performing analytics, or preparing reports. Their operational efficiency has also increased because end-users now have an enterprise landscape view of the data lineage. This is paramount for performing impact analysis and having a transparent and documented data ownership structure across all the critical data, for management and escalation of data issues. Data management becomes a business as usual (BAU) process as the tool is successfully integrated with the enterprise systems.
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