Project snapshot
Our team designed a transformation of a data infrastructure for a financial institution, introducing effective data governance practices and accelerating data management flows. This project initiative helped validate our client’s vision of enhancing data management through a leading data governance platform. The purpose was to create a scalable and governed data ecosystem to streamline data management, reduce onboarding times for data sources, and improve overall efficiency.
Our client is a major US bank with a global presence. In the course of its history, the bank has evolved into a complex network with dozens of branches and lots of digital services. Operating large volumes of various data, our client places significant emphasis on the efficiency, productivity, and security of data management.
Business challenge
While revamping data management flows, the bank needed assistance in designing a more efficient infrastructure and selecting technologies that could help it achieve higher performance and implement effective data governance principles.
The existing infrastructure showed limitations in integrating new data sources, managing data assets, and automating governance processes effectively. Onboarding of new data sources was too time-consuming and affected the quality of services. In addition, the legacy infrastructure generated rather high operating costs, while displaying high latency and inconsistent performance.
Solution delivered
Our team of data engineers, data architects, and DevOps engineers designed a new data processing flow capable of streamlining and accelerating data source onboarding and optimizing operating costs. The platform design included a data governance solution to introduce data management policies and standards and ensure visibility and transparency of data processes. Key elements of the solution included:
- Centralized metadata repository: We integrated the platform with various data sources and systems, creating a centralized repository to manage and govern metadata effectively. This ensured transparency across data assets and laid the foundation for a comprehensive data governance framework.
- Business glossary and data catalog: We established a business glossary containing key business terms, definitions, and policies to ensure consistency. Additionally, we built a detailed data catalog that effectively managed metadata for all data assets, enhancing the discoverability and usability of data.
- Data lineage and profiling: Our team implemented data lineage to track data movement and transformations across different systems, providing complete visibility into the data lifecycle. We also introduced data profiling capabilities to evaluate the quality and structure of data assets, ensuring their readiness for analysis and consumption.
- Integration with Databricks for advanced analytics: The platform was integrated with AWS Databricks to support advanced analytics, improve data processing performance, and facilitate AI-driven insights. We ensured that new data sources were onboarded seamlessly into Databricks, with integrated governance and metadata management.
- Automation of governance workflows: We automated data governance workflows using the Collibra platform’s functionality to handle data-related approvals, issue resolution, and policy enforcement. This reduced manual intervention, increased efficiency, and ensured that governance processes were consistent and streamlined.
- Onboarding data sources: The platform was connected to various data sources, both standard and non-standard, to maintain a central metadata repository. We used specialized modules to onboard non-standard data sources, ensuring they were appropriately cataloged, profiled, and governed.
Business outcomes
With comprehensive testing of the environment design, we helped the client validate the idea of reorganizing their data processes and established that selected software components would be able to achieve set business goals.
The designed platform ensured faster onboarding of data sources, enhanced data processing speed, and reduced manual efforts through automation. By leveraging data cataloging, governance, and metadata management, the solution provided the following benefits:
- Enhanced metadata visibility: The centralized metadata repository allowed for transparent management of data assets, improving overall data quality.
- Improved data lineage and security: Data lineage tracking enhanced transparency, while automated governance reduced risks associated with unauthorized data access.
- Higher operational efficiency: Automation of workflows reduced latency, streamlined data onboarding, and minimized manual intervention, contributing to increased productivity.
The successful execution of this solution demonstrated our ability to deliver a scalable and governed data platform, providing our client with a clear path forward in their data governance and metadata management journey.