Leveraging Data Governance to Ensure Data Quality for Regulatory Compliance

The Power of Comprehensive Data Governance

Mark PriebeNovember 14, 2018

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Let’s face it, government regulations can be a major headache for businesses today, and they’re only growing more challenging and complex. As data has exploded, so too have the number of regulations impacting organizations. From BCBS 239, CCAR, Solvency II, MiFID, to GDPR in May of this year, they all place significant emphasis on data, and soon, more regulations will likely follow.

With GDPR now on the books in Europe, some states in the U.S. are looking to follow suit. California will implement the California Consumer Privacy Act of 2018 (CCPA) on January 1, 2020. In addition, all U.S. states have enacted laws that require businesses to identify personal information and notify customers if the event of a breach. With the implementation of GDPR, there are already those pushing for a similar regulation on the federal level in the U.S.

While complying with these regulatory mandates is a challenge, it can be beneficial from a business and operations standpoint. Identifying personal data and validating that data across an entire data supply chain can help ensure compliance, but it can also help solve other organizational data challenges like data quality issues. Tackling other compliance requirements can also address a lack of data understanding among business users and help organizations build a data-driven culture.

To ensure regulatory compliance and solve data problems simultaneously, organizations require a comprehensive data governance program.

Killing Two Birds with One Stone

 Data governance serves many functions within an organization. It can help organizations track consent receipts, usage, data subject rights requests, and personal data location, as well as ensure compliance with regulations like GDPR. But it also can help foster data integrity and data understanding across the entire organization.

To create a successful data governance program, organizations must align people, processes, and technologies to identify, classify and document information about their data assets. Organizations must build collaboration among data owners and data consumers to eliminate any confusion over what data means or where it resides. By engaging employees from various departments and clearly defining roles and responsibilities among data owners, users, and stewards, organizations ensure a consistent and concrete understanding of data across the enterprise to empower business decisions, while also ensuring they can effectively navigate complex regulatory mandates.

However, building collaboration among diverging lines of business is a tall task, especially when everyone in the organization already has responsibilities outside of data governance. Organizations require a solution suite to simplify the process and create complete transparency across the entire data landscape.

Building Collaboration with an All-Inclusive Solution Suite

Conforming to regulatory requirements while ensuring data quality and understanding requires a comprehensive solution suite with a multitude of capabilities and a thorough data governance program. The solution suite should include capabilities for data governance, data quality, and analytics to enable better control over data and ensure ongoing compliance.

An effective solution must serve the needs of everyone in the organization by not only providing the compliance foundation required by various regulations, but also a data governance framework that enables easy access, usage, and ongoing adherence among data users. This includes establishing a business glossary, documenting the location of data assets, processing data usage and understanding data usage from a legal basis, as well as managing approvals and access authorizations.

It should include highly configurable interfaces, self-service dashboards and easily navigable workflows for organizations to streamline regulatory compliance methods and procedures covering all systems and business processes. This integrated approach allows for compliance collaboration across an entire enterprise and alerts the right people at the right time to potential threats to compliance.

The solution should also conduct high-volume data quality checks such as data profiling, consistency, conformity, completeness, timeliness, reconciliations, and visual data prep to verify the quality of data and ensure continued trust among all data users. By checking the integrity and completeness of personal data, organizations can also process and reconcile it against multiple sources, systems, and usages, facilitating data analysis, and supporting true compliance automation. In addition, analytical capabilities can employ machine-learning algorithms to find hidden personal data hidden across an enterprise, identify compliance gaps, and continuously improve data quality.

By building an all-encompassing data governance program that is part of a comprehensive solution suite, organizations set themselves up for handling regulatory compliance and meeting today’s data challenges.

If you would like to learn more about ensuring regulatory compliance and data quality through data governance, download the data sheet below.

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