Big Data is a marketing campaign. Uttered from the lips of technology companies, including analyst organizations such as Gartner, the term Big Data remains ill-defined. This is intentional. It allows them to claim just about anything they want because their claims can’t be fact-checked if you don’t actually know what Big Data is.
Generally speaking, technology companies use the term Big Data to refer to greater volumes and new sources of data. This, however, is not a new thing. Since the advent of computers, each year we’ve accumulated more data and new data sources. Data didn’t suddenly become big. Big Data is just more of the same, but it is celebrated by technology vendors, analyst groups, and thought leaders as a qualitative break from the past—the newest techno-panacea that everyone must invest in or be left behind. Claims of Big Data’s effects on the world are growing ever larger and more absurd.
In his keynote presentation at Gartner’s IT Expo last week in Orlando, SVP and Global Head of Research Peter Sondergard proclaimed that by the year 2015 a total of 4.4 million jobs will be created worldwide to support Big Data. Not only that, but every new Big Data role in the U.S. (1.9 million by 2015) will create jobs for three more people outside of IT. What does this actually mean? What constitutes a Big Data role? Because the term is so vaguely defined, Gartner can claim that any new job in an IT department or for people who work elsewhere with data in any way is in fact a new Big Data position. This is pure fantasy.
And how did Gartner come up with the 4.4 million job figure? My guess is that, after a long night of drinking, they gathered around the Ouija board and let the spirits (that is, their own drunken imaginations) lead them to the answer.
Notice the irony. Here is an organization of industry analysts talking about analytical technology that is engaging in analytical nonsense. No qualified data analyst would make such absurd and groundless predictions. Either the so-called analysts at Gartner have never been trained in data analysis or they are fabricating predictions that serve their own financial interests. Most likely, it’s both. CIOs who buy into these prognostications are either naïve or are, like Gartner, motivated by self-interest. After all, chasing the latest technology is what keeps CIOs employed.
Organizations all over the world rely on groups such as Gartner to guide their IT investments. Are they getting objective and reliable advice? Far from it. Gartner has no incentive to discourage organizations from investing in IT. They make their money by keeping us convinced that we can’t live without the latest technologies, regardless of whether they’re actually needed or actually work. The truth is, analyst organizations such as Gartner are in bed with the very technology vendors whose work they supposedly monitor and critique. They’re having a wild orgy in that bed, rolling in cash, but it is only the end users who are getting screwed. Essentially, Gartner and the like operate as extensions of technology company marketing departments. Gartner is creating demand for its clients’ products and services (yes, the very technology companies that these analyst organizations monitor—supposedly in an objective manner—are their clients, who pay dearly for their support). These products and services aren’t usually needed, they are often ineffective, and in the case of Big Data, they’re ephemeral. Have you noticed that every business intelligence vendor has suddenly become the leading Big Data company without changing anything that they do? Just slap a new name on business as usual and you can get the world to line up at your door.
Look past the marketing hype for analytical (data sensemaking) products that actually work. It doesn’t matter whether they’re called Big Data, analytics, or just plain data analysis tools. What matters is that they help you find the signals that exist in the midst of all that noise in your data and make it possible for you to understand those signals and use that understanding to work smarter than before. Demand that vendors show you how their tools can be used to glean real value from your own data. Ignore their claims and demand evidence. Make them show you how you can make better decisions using their products and services. Unless they can provide that, you don’t need what they’re selling.