Melissa Data Partners with Pentaho
The integration of Melissa Data with Pentaho's Big Data Integration and Analytics platform will bring data quality to Hadoop environments.
Posted Apr 25, 2016
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Melissa Data, a provider of global data quality solutions, today introduced flexible, scalable data quality to the Hadoop framework for storing and processing Big Data in a distributed environment.

Fueled by a close integration with Pentaho's Big Data Integration and Analytics platform, Melissa Data's global data quality tools and services can be scaled across the Hadoop cluster to cleanse and verify billions of data center records.

Pentaho Data Integration offers drag-and-drop data integration coupled 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, processes can be automated through the Melissa Data component for enhancing, verifying, correcting, standardizing, or deduplicating customer records. Options include full-spectrum data quality that supports the entire Big Data lifecycle. These operations can also leverage Hadoop data processing frameworks.

"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 of enterprise sales and strategy at Melissa Data, in a statement. "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."

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