Creating an Agile Data Quality Strategy for Effective Regulatory Compliance

Many businesses are crafting their data quality strategy to help achieve regulatory compliance.

As both individuals and nations become more concerned about privacy and security, it is certain that data-focused regulations will continue to grow in number, breadth, and depth. This has many implications for businesses.

Get off the whack-a-mole compliance treadmill with data quality strategy

Some companies put in place technology and mechanisms specific to each regulation with which they must comply. While this approach does bring organizations into compliance, it is a narrowly focused approach with limited benefits, and puts organizations in a position of playing catch-up as additional regulations are passed.

A broader approach that offers wider benefits is to invest in new ways to catalog, understand, measure, and monitor your data so that you can make confident assertions that can be proven to regulators consistently over time.

An agile data quality strategy is perhaps the most productive way to invest in a compliance architecture and get off the expensive whack-a-mole compliance treadmill. With an approach that prioritizes data quality, companies can measure how well they’re complying with regulations at a granular level while at the same time driving greater business value from their data.

Read this eBook to explore how an agile, iterative data quality strategy can help your organization streamline compliance and proactively face new regulations with confidence.

When companies think of compliance, they usually think first about government regulations like the European Union’s GDPR. Other regulations apply to particular industries, such as the Comprehensive Capital Analysis and Review (CCAR) and Dodd-Frank Annual Stress Testing (DFAST) for financial services or HIPAA for healthcare. These regulations each have their own compliance requirements.

To work with their business partners, companies must also conform to industry standards like electronic data interchange (EDI) or SWIFT messages. While not compliance from a legal standpoint, these standards require that the data exchanged all have certain agreed-upon characteristics for interactions with business partners.

Ebook: Creating an Agile Data Quality Strategy for Effective Regulatory Compliance