Tamr has announced the release and availability of its Spring 2019 data unification platform. The update is headlined by Persistent IDs, a new suite of data mastering workflow capabilities. The features provide users with better reporting on how clusters of related records change over time, as well as track lineage, and publish results to downstream systems. There are also new visualization capabilities that enable those doing data preparation to review cluster changes before publishing master data to business intelligence software.
Tamr is also introducing Golden Records as a core feature of the Unify platform, and 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. There’s also data transformations for pipelining. This enables users the ability to develop, test, and execute data transformations through the user interface.
Tamr Unify now includes a Python client for data scientists who want to produce analytics as well as IT personnel wanting to automate workflows using a familiar language. That client is now public on GitHub. A new active learning for categorization projects add-on enables the Tamr system to identify the highest impact records for humans to review and label as training data, delivering the maximum uplift to the accuracy model with less effort.
In a statement to Solutions Review, the company’s Head of Product Mark Marinelli told us: “With this new release, we continue to remove the barriers between large organizations and their most critical data assets, ” said Mark Marinelli, Tamr’s head of product management. “These new capabilities advance our agile mastering offering on many fronts, combining machine learning with human expertise to deliver more accurate results, more quickly, from more data, when compared to traditional MDM and ETL technologies.”
To learn more about Tamr Unify Spring 2019, check out the online product documentation.
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