Case Studies
Data Quality Instrumentation

Project:
Data Quality Instrumentation for a Global Private Banking Institution

Current State:

A Global Private Banking Institution is experiencing rapid data growth in both volume and substance (structured and unstructured).  Data quality has been identified as a key initiative for improving the firm’s standing in the eyes of its financial advisors and clients.

Challenge:
Construct a platform for instrumenting a data quality reporting solution for the Private Banking business division based on an architecture that could be pointed at enterprise-wide data sources in a scalable manner. Utilizing a rules management framework, the data quality solution should incorporate, define and implement technical and business rules to proactively monitor, track, and report on data quality statistics over time. By leveraging dashboard and scorecarding technologies, the platform must also make data quality metrics and measures widely and interactively available at both summarized and granular levels.

Approach:
This program was divided into multiple phases in order to quickly and effectively deliver high-quality and tangible solutions.  The first phase included instantiating key components of the technical architecture as well as identifying and defining key business rules around which to measure data quality. Business-contextual impact measures were created and combined into a composite data quality score, allowing the most impactful data quality issues to bubble to the top. The initial phase of this program concluded with the delivery of an initial set of data quality rules implemented on the data quality solution architecture, the results of which were reported in the DQ dashboard at multiple levels of granularity.

Next Steps:
Exusia continues to work with the client on this project, expanding coverage of the DQ platform by bringing additional data sources and business units online. To facilitate this expansion and broader coverage, key components of the architecture are being extended, including integration with the firm’s application and data security model, enhancing the DQ management framework to allow users to define their own data quality rules, and augmenting the integrated UI to deliver a more robust user experience. Finally, as a future direction for the overall solution, a set of data quality services will be implemented supporting corresponding policy, procedures, and resources to support data remediation as a follow-on function to data quality reporting.

Exusia Point of Contact:
Craig Bliss, Partner

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