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Why Bigger Data Isn't Always Better

Look past the numbers when evaluating data

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In this tip sheet you will gain a better understanding on:

  • How to effectively evaluate quality, coverage and accuracy of data
  • The types of lifestyle and demographic attributes needed to achieve your overall objectives
  • The importance of evaluating the quality of the data

As a data science or marketing professional, when you’re offered more consumer data — more records, more identities and more attribute fields — it’s only natural to be interested. But more data may not always be useful.

By reading more, you will gain the knowledge you need to work with your data partner to help you understand the actual content, context and use of the data as well as the options that are right for your unique needs.

Why bigger data is not always better tip sheet