Tresata Releases TREE 3.3
CHARLOTTE, N.C., June 5 – Tresata announced the release of TREE 3.3, its third generation of its most successful software application that has been used by both financial services and retail industry giants to integrate disparate datasets in Hadoop at a segment of one.
TREE is the only 100% Hadoop-powered software application that collects, curates and collapses multiple datasets ranging from transactional data, market data, customer service data and social network data and is able to resolve all critical variables to a unique segment of one, even when no unique identifier exists across all datasets.
With this latest release, TREE now includes the ability to run in real time and a feedback loop that allows a business user to verify and tune the results of TREE’s entity resolution engine.
“We believe the ability to integrate and resolve data from any source and of any size to a segment of one is a critical capability for any enterprise that wants to monetize big data,” said Abhishek Mehta, Founder and CEO at Tresata. “Once you have a deep understanding of your customers across all their interactions, then you can help them make decisions that are in their best interest. That journey starts with TREE.”
In the last three years, TREE has been successfully deployed by customers across a range of business opportunities: monetize corporate payments data at a large global financial services institution, integrate social and transactional data at a large retailer, analyze wealth management data at a private bank and build the first comprehensive credit profile at a data integrator.
“As next-generation predictive analytics experts, Tresata enables companies in retail, financial services and other data-intensive industries to maximize the potential of all their data, improve customer service and accelerate growth,” said John Kreisa, vice president of strategic marketing at Hortonworks. “With TREE 3.3 running on HDP 2.1, customers are now able to derive critical business insights that advance their business, as well as find more opportunities to monetize their big data solutions.”