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What is Data Unification?

To those unfamiliar, data unification may seem insignificant. After all, it can’t be that hard to unify data, right? Unfortunately, this is a huge misconception. Data unification is an incredibly complex process and one of the biggest challenges many large…

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A Guide to Machine Learning for Data Stewards

Leading-edge consumer technology companies, such as Google, Amazon, and Netflix, have demonstrated the impact that machine learning can have on the customer experience. These brands have become some of the most valuable in the world by delivering experiences that feel…

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How to Save $10M+ with Supplier Mastering

Over the past 5 years, Supplier Mastering has become one of the most common problems that we solve for our customers. Some people refer to this as the “Supplier 360” problem. Others just say, “we have poor visibility into our…

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Why Machine Learning Trumps Rules

Enterprise data and IT professionals often ask us: “Why do I need a solution like Tamr? We already have rules-based systems for data mastering.” It’s a valid question, and the answer is vitally important for enterprises that want to thrive…

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You Can’t Be Customer-Centric With Siloed Data

Consumer product companies live by their customers, but their data is often anything but customer-centric. In many cases, there are multiple entities that are the same person, or data is incomplete. It might be perfectly understandable that someone who bought…

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Introducing Steward: The First Issue Tracker for Data

Do you have a data quality process that actually works well? We’ve heard, “no”, almost unanimously across enterprises. Most often, data quality issues get raised through a process that looks like this: These sorts of emails provide little to no…

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Introducing Supplier Mastering as a Service

It’s no secret that enterprise data has its challenges. It’s messy, difficult to use, and can feel overwhelming to understand. Driving improved business outcomes from this data can feel like an insurmountable task. This is particularly true in procurement, which…

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