Tamr Launches Fall 2019 Data Unification System to Power Breakthrough Analytic Insights

By on

According to a new press release, “Tamr, Inc. announced today the general availability of the Fall  2019 release of the company’s patented data unification system.  Tamr is a data integration software platform that uses supervised machine learning to unify data silos. It enables data engineers (who aren’t data scientists) to harness the power of machine learning to build automated pipelines that integrate, master, and classify disparate, dirty data. With the Fall 2019 release, Tamr offers cloud support, geospatial mapping and additional enhancements to make it faster and easier to unify large numbers of heterogeneous sources.”

The release continues, “The adoption of cloud computing continues at a phenomenal pace and is fast becoming the default at companies of all sizes.  With a growing number of high-profile companies implementing cloud strategies and most organizations using at least some form of cloud services, organizations will continue to accelerate migration of their computing environments to the cloud and at an accelerated rate.  Tamr Fall 2019 offers support and capability for Amazon Web Services, Google Cloud and Microsoft Azure and provides a flexible and powerful way for users  to find, gather, unify and format data from many disparate sources.”

Filip Salaets, IT manager customer & retailer data with Toyota Motor Europe, “Tamr’s speed and efficiency in conjunction with AWS’s industry-leading scalability and security has allowed TME to benefit from machine learning in the Tamr data unification platform… As a result, TME has seen a 40% reduction of duplicative customer records allowing for an increase in efficiency and business value.” 

Read more at PR Newswire.

Image used under license from Shutterstock.com

We use technologies such as cookies to understand how you use our site and to provide a better user experience. This includes personalizing content, using analytics and improving site operations. We may share your information about your use of our site with third parties in accordance with our Privacy Policy. You can change your cookie settings as described here at any time, but parts of our site may not function correctly without them. By continuing to use our site, you agree that we can save cookies on your device, unless you have disabled cookies.
I Accept