Best Data Quality Solution

Today, data quality solutions are available in the cloud as software as a service as well as on premise, and support the necessary data integrity for critical systems such as customer relationship management, master data management, data governance initiatives, and database management, as well as for regulatory compliance initiatives—including the E.U.'s new General Data Protection Regulation (GDPR).

With more data streaming in from more sources, in more varieties, and being used more broadly than ever by more constituents, ensuring high data quality is a  high priority.

Customers expect organizations they deal with to contact them with the right name, title, physical location, email address, and social media handle to demonstrate that they actually care to know who they are, and have a high level of attention detail. By contrast, incorrect data can also mean duplicate entries that can make it difficult for vendors to achieve a single version of the truth.

In terms of regulatory compliance, a lack of data quality can result in significant problems for organizations.

Melissa, a provider of global contact data quality and identity verification solutions, recently sponsored research among U.S. companies with annual revenue greater than $10 million about their understanding of and preparedness for GDPR.

The survey uncovered two areas where companies are significantly exposed to legal risk by these new regulations. Penalties went into effect in May, 2018, and non-compliant organizations risk triggering fines of up to 20 million euros or 4% of global revenue, whichever is higher.

According to Melissa, the survey results showed that most U.S. companies do not adequately understand the challenges of GDPR, particularly the "right to be forgotten," guaranteed by Article 17 of the new regulation.

Companies may also have a false sense of security that their current single customer view (SCV) platforms such as customer relationship management (CRM), customer information file (CIF), and master data management (MDM) customer hubs will be adequate for GDPR compliance.

In reality, Melissa says, the strict fuzzy record matching configurations of current SCV platforms were not designed to meet the looser fuzzy match requirements of GDPR.   The survey report includes guidance on strategies to address these GDPR risks, including empowering an individual to oversee GDPR compliance, conducting a GDPR Right to Erasure Risk Audit, and auditing various SCV platforms for their ability to locate all versions of any E.U. resident's record quickly and thoroughly.

Best Data Quality Solution 

Melissa Data Quality


Syncsort Trillium Quality for Big Data

SAS Data Quality

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