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Categories: Hadoop RedPoint

WELLESLEY HILLS, MA–(Marketwired – December 05, 2016) – #RedPointGlobal, a leading provider of data management and customer engagement technology, today announced its Data Management technology has been positioned in Gartner Inc.’s 2016 “Magic Quadrant for Data Quality Tools” report [1]. RedPoint Global has appeared in the Data Quality Magic Quadrant every year since 2012. Evaluating the data quality tools market, the report positions providers of data quality solutions based on ability to execute and completeness of vision. The report defines data quality assurance as encompassing not only technology, but also roles and organizational structures; processes for monitoring, measuring, reporting and remediating data quality issues; and links to broader information governance activities via data-quality-specific policies. The complete report and quadrant graphic are available at:

“We are honored to be recognized by Gartner in the Data Quality Magic Quadrant for the fifth consecutive year,” said Dale Renner, CEO and founder of RedPoint Global. “We believe we are well positioned in this market due to the combined scale, speed, precision and agility of our technology. Our customers appreciate the value they receive, not only in terms of broad product functionality, but also in quick return on their investment in RedPoint.”
With RedPoint Data Management, organizations can access all data types from any source without requiring specialized coding skills — reducing costs and increasing the speed at which organizations obtain critical insights. RedPoint Data Management’s data quality routines execute in an automated production flow inside any traditional database or big data/Hadoop environments, so organizations can perform data preparation without moving data. This reduces the latency between aggregating data and leveraging it in analytics, whether business intelligence, offline or real-time, to drive better and faster decisioning and therefore, results. Additionally, since RedPoint doesn’t require moving data out of Hadoop, data quality functions can be performed in near real-time whereas competitive solutions will take anywhere from 72 hours to two weeks to complete these functions.

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