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Customer Intelligence Blog

Sharing knowledge about gaining and keeping customers

Big Data or Better Data?

April 30 2012 by Shane Helfenberger

Most of you have probably heard the term “Big Data”.  It is a trendy buzzword at many conferences and there are a number of articles and blogs that discuss it as the next big thing.  What exactly is “Big Data” and why should you care?   Most define it as the collection and analysis of large amounts of data to make better decisions and/or provide better direction.   To me, the term speaks to the growth in transactional and other data processing over the past 10-15 years (ex. – Amazon’s recommendations for similar products).   There is much more data available today, which can allow for more precision in BI (Business Intelligence) and other types of analysis.

The problem is that “Big Data” is not the answer.  Quality Data is the answer.

Quality does not seem to be a focus in any of the articles I’ve read recently.  “Small Data” can be even more powerful than “Big Data” depending on the quality of the data being captured.  While it is true that more data can lead to more precision in analysis, the data elements must be clearly defined and validated.  By clearly defining what is important in terms of data capture and developing mechanisms to validate the data, you will ensure that quality data flows through the process, no matter the size of the data.

Altair has 70+ years of combined processing and analytics experience and a scalable network infrastructure so we can help your company navigate any data considerations.  The average company processes 63 Terabytes of data annually.  As a data-centric company, Altair processes nearly as much data on a monthly basis.  Please contact me at tblackman@altairci.com to learn how Altair can help.

  • Jermainebarnett9

    I really like this article but there are two words that should be added to this definition of “Big Data”. I would define it as the collection and analysis of large amounts of “Quality Data” used to make better decisions and/or provide better direction. Without qualified/accurate data, your “Big Data” may really appear “big data”.