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Little Data vs. Big Data: Nine Types of Data and How They Should Be Used

by Jerry W. Thomas  |  
March 17, 2014
  |  10,255 views

In this article, you'll learn...

  • How today's overwhelming volume of data is making it difficult for marketers and advertisers to know which information is significant and which is pure noise
  • How different types of data should be used and for what purposes
  • How small amounts of data, if correctly obtained and properly analyzed, can provide better marketing insight more cost-efficiently

You are not feeling well, so you visit your friendly family doctor. He puts you in a new electronic scanner and generates 28 trillion measurements of your temperature all over the surface of your body. He then saves all of these measurements and, using advanced statistical algorithms and supercomputers, announces that your temperature is 98.6 degrees Fahrenheit. What a relief! Big Data to the rescue.

The Bandwagon

As the Big Data bandwagon picks up momentum, consultants, professors, conference organizers, authors, magazines, blogs, software firms, pundits, crooks, private equity firms, and computer hardware manufacturers are clamoring to get aboard. Rarely has a bandwagon attracted so much attention or so many passengers.

The basic premises of Big Data appear to be the following:

  • More data are always better than less data.
  • Volume, variety, and velocity of data create new sources of potential knowledge and prescience.
  • With Big Data, all questions can be answered: The "why" will finally be revealed to the human race, and the future can be accurately predicted.

Is Big Data an accurate picture of the future, or is it simply a mirage shimmering in the distant desert heat? Is it the pathway to ultimate truth, or is it only a bandwagon of exaggerated promises and illusory dreams?


The truth is that the solution to marketing and business problems—and the identification of strategic opportunities—often lies in the realm of Little Data, not Big Data. You don't have to boil the ocean to determine its salt content. You don't have to eat the whole steer to know it's tough.

The Limits of Data

The preponderance of business data—indeed, all data—in the world is historical data, or "tracking" data, such as financial data, sales data, customer behavioral data, weather data, and inventory data. Virtually all data tend to be backward-looking, analogous to looking in the rearview mirror to steer a car forward.


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Jerry W. Thomas is president and chief executive officer of Dallas/Fort Worth-based Decision Analyst Inc., an international marketing research and marketing consulting firm. He may be reached via 1-800-262-5974, 817-640-6166, or jthomas@decisionanalyst.com.

LinkedIn: Jerry W. Thomas

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Comments

  • by Kip Meacham Mon Mar 17, 2014 via web

    Interesting premise and article. Maybe I missed something, but as I read it, the author makes a compelling case for Little Data being no more affordable or obtainable for small companies than Big Data.

  • by Kip Meacham Mon Mar 17, 2014 via web

    ... at least from a financial/affordability context, that is.

  • by Azana Baksh Wed Mar 19, 2014 via web

    Jerry, very informative Big Data article. With the explosion of big data, companies are faced with data challenges in three different areas. First, you know the type of results you want from your data but it’s computationally difficult to obtain. Second, you know the questions to ask but struggle with the answers and need to do data mining to help find those answers. And third is in the area of data exploration where you need to reveal the unknowns and look through the data for patterns and hidden relationships.

  • by Jed Jones Wed Mar 19, 2014 via web

    Thanks, Jerry. I agree with one of your main premises: that "little data" remains in many ways more useful, and certainly more accessible, for most day-to-day business applications, than does the over-hyped big data.

    However, I have to disagree with your statement that "but most historical data are of limited value in predicting the future." Certainly, to your point, we can never "predict the future." However, if we take your premise to its logical conclusion, then we cannot use ANY data at all in a useful manner to make informed business decisions. What is data analysis if it is not the analysis of past data for application to future decisions? (Even a car speedometer is technically showing us "past" data - and it indicates that we will likely be traveling at around that same speed over at least the next half second or so). While we cannot predict the future with data, we can certainly find indications of one or more likely possible futures, based upon past data.

    Nate Silver's "The Signal and the Noise" is a great reference for more on this entire topic. It explores both the opportunities and the limitations of using past data to predict the future. He favors an approach that enfolds multiple types of references, rather than over-emphasizing a single algorithm.

  • by Louis Tremblay Fri Apr 4, 2014 via web

    Great article and well balanced view on little data vs. big data.

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