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.
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.