Many think it’s an important concept, and some think it’s revolutionary, but almost everybody wishes for a better, more descriptive name for it.
One finding has been common in all the research I’ve done on big data over the last few years: Nobody likes the term. Many think it’s an important concept, and some think it’s revolutionary, but almost everybody wishes for a better, more descriptive name for it. Some managers are objecting only to the hype around the big data buzzword, but I believe many executives simply yearn for a better way to communicate what they are doing with data and analytics.
Part of the problem is that “big data” just doesn’t describe the phenomenon very effectively. Here are several reasons why the term is highly flawed:
For these reasons, and perhaps others, the term just doesn't suit. In one survey I saw recently, over 80 percent of the executives surveyed thought that the term was overstated, confusing, or misleading. They liked the concept, but hated the phrase.
So why don’t we simply stop using it? The problem is that as a society we like to attach revolutionary new labels to things that have been around for a while, but all of a sudden became too big to ignore. We've had various forms of large-volume, unstructured data for a couple of decades now, but the world at large just noticed. The other problem is that there is no obvious alternative as an umbrella term for the relatively new types of data that are increasingly common today. We could try to call it “petabyte or more data,” “all data,” “size doesn't matter data,” or just “data,” but none of these terms quite captures it, and they don’t trip off the tongue either.
What to call this phenomenon probably isn't your company’s most important problem now. However, the continued use of “big data” in conversations within and outside your organization is likely to be causing confusion. If you tell someone you are working on a big data project, you are not really providing much information about it other than that you know the latest, coolest corporate lingo. And it’s not as cool as it used to be anyway. I doubt that your employees, your board of directors, or your investors will take much notice if they hear your company is doing something with big data. Don’t count on it to give your stock price a bounce either.
One approach that is much more descriptive is to deconstruct “big data” a bit in order to signal to stakeholders what you are really interested in doing with these new types of data. You might describe in greater detail the following types of project attributes:
If instead of saying, “We’re working on big data,” you say, “We’re extracting customer transaction data from our log files in order to help marketing understand the factors leading to customer attrition,” you will have used more syllables, but you will be much more informative. In addition to providing clarity about your intentions and strategies, this approach avoids endless discussions about whether the data involved are big or small. In fact, the most valuable applications will use a combination of both big and small data, structured and unstructured formats, internal and external sources, and so forth.
I don’t actually think that it’s criminal to use the term “big data,” and you may have noticed that I used it a few times in this essay. It’s not easy to avoid, and there isn't a great substitute that captures all the things embodied in the phrase. However, taking the time to employ a few more descriptive terms and descriptions will get your objective across much more effectively.