Tamr Launches Spring 2019 Release of Flagship Data Unification System

Tamr Inc., announced the general availability of the Spring 2019 release of the company’s patented data unification system. Unlike traditional data integration approaches, Tamr’s software is purpose-built to leverage machine learning, human knowledge, and  where appropriate -rules to solve the hardest data integration challenges.  As a result, enterprises are able to create new, unified data assets that fuel breakthrough analytic insights and operational improvements to accelerate their digital transformation initiatives.

Unify was initially conceived by Turing Award winner Dr. Michael Stonebraker and his co-inventors who published their research in early 2013 about the Data Tamer System for tackling large scale data curation challenges. Tamr was founded shortly after that to commercialize the research with initial backing from NEA and Google Ventures, two of the most successful investors in the data management market.  The company’s innovative approach to unifying myriad diverse data sources has attracted many large customers, several of which have also become investors, including Thomson Reuters, Samsung, GE, and MassMutual.

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“Tamr’s Spring 2019 release extends our advantage over traditional data integration tools,” said Mark Marinelli, Tamr’s head of product management.  “The new capabilities in this release delivers a powerful alternative to MDM and ETL for large organizations seeking a faster, more accurate, and cost-effective way to unite, master, and classify data from their many siloed systems.”

“Having worked first-hand with Tamr, the company is driving innovation in the data management market with its machine learning-based approach to data unification,” said Mark Ramsey, founder of data and analytics consultancy Ramsey International and former SVP Data Officer for R&D, GlaxoSmithKline. “The capabilities in this latest release will enable new and existing users to extract more value, more quickly, from their siloed data assets.”

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New Features in Unify Spring 2019

Persistent IDs – Persistent IDs enable a new suite of data mastering workflow features that provides users with enhanced reporting on how clusters of related records change over time, track lineage, and publish results to their downstream systems. New visualization capabilities enable data preparers review cluster changes before publishing master data downstream to apps like PowerBI and Tableau.

Golden Records – Tamr introduces Golden Records as a core feature within Unify. A golden record or “single version of truth” represents the best data available about an entity and where users will turn when they want to ensure they have the correct and complete version of master data for an entity.

Data Transformations for Pipelining –  Tamr enhances the curation process by giving users the ability to develop, test, and execute data transformations at scale through the user interface. Along with time and cost savings, the accuracy and usability of the unified datasets are greatly enhanced with transformations making the data invaluable for all downstream applications. To learn more, read this blog post.

Python Client – Python Client for Tamr Unify is now public on GitHub and for both data scientists who want to produce robust, trusted analytics as well as IT personnel wanting to automate workflows using a familiar language.

Active Learning for Categorization –  Building the most accurate machine learning powered classification model with a minimum amount of training labels just got easier with Tamr’s new active learning for categorization projects. The Tamr system identifies the highest impact records for humans to review and label as training data, thus delivering the maximum uplift to the accuracy of the model with the least amount of effort.

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