Melissa Data Launches Partner Program for Professionals

Quality testing of data can be a lonely job. But networking and sharing knowledge within the channel is set to become a little easier in the new year, thanks to a program Melissa Data has launched to bring industry experts together around the company’s data quality platforms. Data analysts may still find themselves sipping their coffee in solitude, but the network could make it easier to leverage the growing array of tools that are emerging to meet the needs of the next generation of Big Data.

Melissa Data‘s Most Valuable Professional (MVP) program is another way for the company to pitch its data-quality products. But beyond marketing, the program offers tangible benefits for data engineers and industry experts, to whom it provides training, access to data-quality tools and networking opportunities.  Joining the program is free.

The MVP program aims to cater especially to professionals who work with Oracle products, such as members of the Oracle ACE community. As Melissa Data representative Joseph Vertido said in a statement:

Industry experts who join the MVP program receive free, non-commercial licenses for Melissa Data’s data verification products. The company also offers cash incentives for referring new members to the program in the form of a 15 percent referral commission MVP members receive on new business, according to Melissa Data representatives.

Melissa Data has been around for a long time–since 1985, in fact, well before most people could even envision the kind of information verification and validation challenges organizations face in today’s world of Big Data. But the company has been working hard lately to reach out to channel partners. Last month, it announced a deal with open source Big Data vendor Talend to integrate its address-verification tools into Talend products. The MVP program unveiled this week represents another step toward consolidating Melissa Data’s role in providing data quality solutions as organizations increasingly realize that ensuring the accuracy and integrity of data is just as important as building complex infrastructures to store the information.