Tamr Single Page Overview

Enterprise Data Unification Powered by Machine Learning Tamr’s solutions enable our customers to achieve transformational analytic and operational outcomes by taking a fundamentally different approach to the age-old challenge of data integration. We attack the enterprise data variety problem —…

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Tamr Technical Overview

Tamr was founded to tackle large-scale data management challenges in organizations where extreme data volume and variety require an approach different from legacy technologies. Whereas most traditional solutions focus on top-down, rules-based methods for managing data, Tamr focuses on a…

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Scalable Data Curation and Agile Data Mastering

Traditional data management practices, such as master data management (MDM), have been around for decades – as have the approaches vendors take in developing these capabilities. For the longest time, the problem set being addressed was the management of data…

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The Seven Tenets of Scalable Data Unification

This paper defines the concept and process of data unification and compares different technical approaches to achieving the desired end-state of clean, accurate, consolidated data sets. It then proposes seven tenets that must be considered by data management practitioners who…

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Building the Digital Thread Across the Enterprise

Building the Digital Thread Across the Enterprise Today’s Chief Data Officer must ensure that hundreds of data sources across the enterprise are clean, consistent and being used properly to power transformational analytics. Large enterprises such as GE, Toyota Motors Europe…

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Tamr Platform Overview

Quickly Uncover Insight From All Enterprise Data Data is the most important asset an organization has at their disposal. It can be used to help make tactical decisions as well as guide more strategic, transformational ones. Although the importance of…

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Tamr on Google Cloud Platform

Business analysts and application developers are under increasing pressure to generate clean, comprehensive datasets for analysis to drive business value. Without high quality, unified data, downstream analytics are ineffective and, in most cases, time is of the essence when generating…

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