In 2019, it’s no longer a question of whether to become an analytics-driven organization, but how.
What is data stewardship and what are the areas where machine learning can help data stewards? Download our guide to machine learning to find out.
In this chapter from the book Making Databases Work: The Pragmatic Wisdom of Michael Stonebraker, Ihab Ilyas discusses the academic project that eventually become Tamr.
In this chapter from the book ‘Making Databases Work’, Nik Bates-Haus discusses his experience recruiting Tamr’s core engineering team and building the first release of the company’s commercial product for data unification.
In this chapter from the book ‘Making Databases Work’, Andy Palmer discusses what it’s like to run a company with Michael Stonebraker.
The process of migrating your data to new software is a lot like moving into a new house: you want to consolidate and clean. That’s the role played by Tamr’s data unification and cleaning services during a migration.
Learn how enterprises have applied three generations of AI to address data unification challenges.
New compliance changes have brought about the need for effective solutions that enable smooth, ongoing operations and robust risk analytics for trade reconciliation.
As more organizations look to leverage data as an asset, the limitations of traditional MDM solutions have become a pressing challenge. Learn how Agile Data Mastering solves this challenge.
This report from O’Reilly covers: starting with the business question, understanding your data, selecting the data to use, and more.
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 —…