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Guide to Data Enrichment:

What It Is, Why It Matters, and How It Enhances the Power of Your Data

Enhance your internal data with trusted external sources.

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Build the Business Case for AI-native MDM

Discover how to connect the dots between challenges, opportunities, and measurable impact. Start building your AI-native MDM business case today.
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Get Your Copy

For more information, please view our privacy policy.
Read the ebook

Build the Business Case for AI-native MDM

Discover how to connect the dots between challenges, opportunities, and measurable impact. Start building your AI-native MDM business case today.
Download Now
Oops! Something went wrong while submitting the form.

Overcome obstacles to data enrichment by asking five key questions

  • What data attributes do you need—and how do you identify them?
  • How do you assess the sources you need?
  • How do you integrate third-party data with your own internal data?
  • How do you get value—and how do you measure it?
  • How do you make the process continuous?

 
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Overcome obstacles to data enrichment by asking five key questions

  • What data attributes do you need—and how do you identify them?
  • How do you assess the sources you need?
  • How do you integrate third-party data with your own internal data?
  • How do you get value—and how do you measure it?
  • How do you make the process continuous?

The Importance of Data Enrichment

Companies realize greater value from their internal data once it’s cleaned and mastered. But here’s a secret that not all companies have realized: Getting the best version of your data requires looking outside your organization as well. That’s why, to successfully improve data quality, organizations must link their valuable, internal data with trustworthy external data provided by third parties, vendors, or public data sources via data enrichment. 

In our guide, you’ll discover what data enrichment is, why businesses need it, and how to do it effectively using Tamr’s AI-native master data management (MDM) solution.

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