Melissa, a leading provider of global contact data quality and identity verification solutions, today advocated native data quality in Oracle platforms. Melissa’s active data quality tools and services are featured natively in CLEAN_Address®, an Oracle-validated, integrated address verification solution for numerous editions of PeopleSoft Enterprise, JD Edwards EnterpriseOne, and E-Business Suite platforms. Melissa points to active data quality, seamlessly integrated into Oracle platforms, as the essential driver of trusted analytics and overall ROI of enterprise data initiatives.
CLEAN_Address protects and enriches data to not only create a complete customer view, but also to fully capitalize on the built-in value of an enterprise-grade data quality infrastructure. Melissa will feature CLEAN_Address at COLLABORATE 18, #C18LV, booth 1100, April 22-26, 2018, at the Mandalay Bay Resort and Casino in Las Vegas.
“Data quality initiatives are the backbone of the enterprise – the basis for analytics and decision-making. Yet the investment in Oracle applications is only as valuable as the data they contain,” said Bud Walker, vice president, enterprise sales and strategy, Melissa. “That is where active data quality adds tangible value to Oracle environments. Users can automatically verify vast amounts of information, via native, Oracle-validated tools and services that run in the background at the point of entry and throughout the data lifecycle. Bad data never enters the system and data can be enhanced in real-time or batch mode, using any combination of integrated tools that fit specific enterprise needs and platform requirements.”
Active data quality taps into Melissa’s smart, sharp tools and authoritative multisourced data in Oracle environments. Oracle users can verify a person’s identity in real-time, while cleansing, standardizing, and enriching the customer record. Organizations are empowered worldwide to increase the value of each customer relationship, as well as protect the enterprise investment in data management.