The Importance of Data Quality Amid Digital Transformation

Data quality is the foundation for a modern, data-driven enterprise; if it’s data-driven, the data itself must be thoroughly and effectively handled in order to invite successful business operations.

DBTA hosted a webinar, sponsored by Melissa, titled “The Growing Challenge of Data Quality in the Era of Cloud and Analytics,” featuring speakers Joe McKendrick, research analyst at Unisphere Research, and Bud Walker, VP of strategy and enterprise sales at Melissa, to discuss the issues with ensuring data quality among disparate and complex enterprise landscapes.

McKendrick explained that there is an overarching disconnect between what an enterprise needs to do to ensure good data quality, and what business leaders are willing/have the resources to execute. As digital transformation is rising in necessity, moving to the cloud introduces a plethora of challenges that inhibit data quality. Not only that, the data is siloed, derived from disparate sources, existing in many formats and platforms, and requires a particular skill level to be handled effectively. Business leaders are left with a weighty and expensive data quality problem that infects many layers of a data-driven business.

In a survey examining 224 companies of all sizes and industries conducted by Unisphere Research, a mere 33% of data managers are completely confident in the quality of their enterprise data. More than four in 10 companies lack any sort of data quality efforts, and after moving to the cloud 20% of companies surveyed reported that data quality challenges had significantly increased. These statistics represent a need for tools and systems that can promote better quality data, without draining enterprise resources.

Walker introduced Melissa’s line of solutions and products as the answer to improving enterprise data quality. Their tools, addressing critical steps in quality assurance like profiling, cleansing, monitoring, parsing and standardization, enrichment, and matching of data, aim to address the growing challenges of data quality in the face of digital transformation. Melissa has various forms of solutions, ranging from on-premises APIs, cloud APIs, to SaaS offerings. Address verification, identity verification, data updating, deduplication, and data enrichment are only some of the services provided by Melissa to improve data quality throughout an organization.

To learn more about the challenges of data quality and Melissa’s solutions, you can view an archived version of the webinar here.