Melissa Data, a provider of global contact data quality and address management tools, is bringing its solutions to the Hadoop framework for storing and processing big data in a distributed environment.
Enabled by a partnership with Pentaho, a Hitachi Group Company, and integration with Pentaho's Big Data Integration and Analytics platform, Melissa Data's data quality tools and services can now be scaled across the Hadoop cluster to cleanse and verify data center records. The partnership will allow IT and data managers to leverage the distributed computing power of Hadoop to handle rapidly the burgeoning data volumes feeding master data management systems.
"Consistently excellent data quality is essential to protect and maximize the long-term value of analytics, yet cleansing the vast number of records on a Hadoop cluster is not an inherently simple task," said Bud Walker, vice president enterprise sales and strategy, Melissa Data. "By pairing data quality with Pentaho Data Integration, users can quickly automate sophisticated data quality initiatives - capitalizing on the potentially massive scope of a Hadoop system to optimize business intelligence and reporting."
Pentaho Data Integration offers intuitive drag-and-drop data integration with data-agnostic connectivity, and is designed to deliver analytics-ready data to business users from any source. Coupled with Melissa Data's integrated data quality tools available via API or local web service, users are able to eliminate the coding and programming required to achieve Hadoop data quality. Processes can be automated through the selected Melissa Data component for enhancing, verifying, correcting, standardizing or deduplicating customer records. The options can also leverage Hadoop data processing frameworks, further maximizing the investment in Hadoop infrastructures.
Image courtesy of Shutterstock.