A few New Year’s data resolutions

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Since now is the time when we reflect on the past year and make resolutions for next year, in this post I reflect on my Data Roundtable posts from the past year and use them to offer a few New Year’s data resolutions for you and your organization to consider in 2015. The following list is numbered for reference purposes, not priority:

  1. Consider the perspective of others — Master data management (MDM) is often singularly focused on creating a single version of the truth, i.e., a single view of master data entities. There are many business needs for this view, but there are also business needs for other viewpoints you need to consider too.
  2. Remember quality is relative and variable — Perspectives about data quality are relative to a particular business use, and user, of data. Data quality standards also vary. One user’s good data may not be good enough for another user. And sometimes, especially with external data, bad data is as good as you can get.
  3. Don’t just do data to do it — We have become so addicted to doing things with data that we often don’t stop to ask ourselves why we are doing it. Therefore, in the new year you should resolve to only collect, measure, and analyze data if it helps you make a better decision or change your actions.
  4. Don’t trip on the trap of correlation — Big data is big on correlations and many of those correlations will be meaningless coincidences. However, some correlations are clever traps confirming the biases we bring to what we find in data. Lean against your biases to avoid tripping on the trap of correlation.
  5. Question everything, especially data — It’s no question that the number of business disciplines becoming data-driven is increasing. While this is a laudable achievement, don’t let data drive you without questioning where it is going, and where it has been. Don’t be blindly driven by data. Question everything.

Happy New Year!

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Jim Harris

Blogger-in-Chief at Obsessive-Compulsive Data Quality (OCDQ)

Jim Harris is a recognized data quality thought leader with 25 years of enterprise data management industry experience. Jim is an independent consultant, speaker, and freelance writer. Jim is the Blogger-in-Chief at Obsessive-Compulsive Data Quality, an independent blog offering a vendor-neutral perspective on data quality and its related disciplines, including data governance, master data management, and business intelligence.

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