We are at an inflection point in the financial services industry. The evolving and overwhelming demands of regulatory compliance have forced organizations to acknowledge the need for data governance and most are developing their strategy.
Justifying the capital investment to harmonize data across these sources is challenging and many organizations are forced to get by with expensive, labor intensive “spreadsheet enabled” processes. This error prone and expensive approach is not sustainable as labor costs increase and fines escalate.
The good news is that Data Governance does not have to be a tax on the business. In fact, smart organizations recognize it as an opportunity to create a powerful data ecosystem that can be a valuable asset to the organization beyond regulatory reporting by supporting business transformation and driving new revenue. Harmonized, high-quality, well-governed data is not just for regulatory compliance – it is an essential enabler for competitive differentiation.
Cambridge Semantics has developed an approach to data governance based on the Smart Data Lake® solution to harness this opportunity.
Business Drivers
BCBS 239 is one of the key drivers for data governance initiatives, especially in Tier 1 institutions, and it is can be described in four key categories:
To comply with the BCBS 239 principles requires an unprecedented level of data governance and operational activities including:
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Solution: The Smart Data Lake
Retroactively applying these requirements to an existing infrastructure is a monumental task. Fortunately, there is an emerging approach which allows an organization to meet the regulatory requirements, provide a foundation for a robust and valuable data ecosystem, all while leaving existing processes and infrastructure in place. That is the Smart Data Lake.
The Data Lake is a modern approach to enterprise data architecture that provides a great way to rapidly and inexpensively assemble large volumes of unfiltered data for management and analytics. Leveraging cheap storage and commodity hardware, the data lake offers an unprecedented opportunity to democratize access to enterprise data. However, the data lake comes with its own challenges:
Leading organizations are turning to semantic models and tools to address these challenges, hence the Smart Data Lake.
There are several main advantages to Smart Data Lake approach:
1. Industry Standards Based Data Harmonization
2. Model Driven
3. Tools
4. Data Re-use
A critical advantage of the Smart Data Lake is data re-use. By harmonizing your data across diverse sources and describing it in business terms, you can it easily make it available for diverse use cases beyond regulatory reporting. Self-service tools allow business users to select, combine and query any data set in the lake (based on entitlement). This opens up the data for customer, revenue, fraud and other use cases.
Smart Data Lake Characteristics
Conclusion
Regulatory reporting requirements are driving the adoption of data governance. Smart institutions recognize this as an opportunity to leverage emerging capabilities like the Smart Data Lake to create a data ecosystem that can not only satisfy the regulatory reporting needs but also create a data platform that differentiate them in the market.
To learn more, watch our webinar "Applying Data Engineering and Semantic Standards to Tame the 'Perfect Storm' of Data Management".