Big Data— A Take Five Primer
Revelation, Desperation, and Buzzword Du Jour
5 Seconds -
Big data is a term that describes the large volume of data — both structured and unstructured — that inundates a business on a day-to-day basis. by SAS Institute
5 Minutes -
The remainder of this article is developed to provide you with perspective and resources to build your understanding of Big Data.
History
The internet credits Doug Laney with popularizing this term in 2001. Like any good analyst he did so by defining it. SAS Insitute does a wonderful job of succinctly presenting a summary of Doug’s original definition:
The reality is that Doug, like any good analyst, created a simplified model to help develop insight around the implications of instrumentation, data collection, and data storage that were outpacing CPU and human understanding. He also created a new buzzword, although I personally think his “Iron Triangle” was a catchier phrase.
A Starker Reality
Big Data has sadly pushed data analytics beyond our means. This is the revelation that makes the phrase so pervasive, there is just no better way to explain it… yet. Worse still for our understanding, Laney and others were part of a sales culture aimed at selling insight and software to the masses. You might not understand Big Data, but the sales machine was hell bent on making you aware just how important it is!
This led to an excellent analogy:
Kudos to Dan Ariely. I am not sure if he actually penned this adage, but the most of the internet sure thinks he did.
Desperation and Revelation
These two terms do a very nice job of summarizing Big Data. It is the revelation that modern infrastructure is currently outpacing human understanding (no worries — it is a very cyclical thing). It the embodiment of a desperation to alter that dynamic. It is also the desperation of a sales team to sell something nobody quite understands and the revelation that selling Big Data solutions can be done on an emotional level, if you just convince everyone that everybody else gets it. And of course they do it everyday… sometimes twice. :)
5 Hours -
The web is filled with material on Big Data. Not surprisingly, most of it is a rolling sales pitch. To dig through much of it, you may need to subscribe to a few newsletters and submit to some amount of data analytics sales spamming. O’rielly offers a nice one pager here: disclaimer — I did not download the report, my inbox is full.
Another useful resource is Dataconomy. They have plenty of targeted articles that will help you on your way.
5 Days -
In typical Five Minute Primers, this is where we reference you to great books on the topic. Sigh…
If you know of any, drop them in the comments below. To date, nothing I have read has impressed me enough to recommend it. This topic is just too young and too self-serving. Even the few case studies that are worthy of a long read fail to show that Big Data was really the driver of insight. Most of these fall into the category of standard analytic practice finds value among massive data repository… that is NOT Big Data.
5 Weeks -
Post graduate programs and online certifications are all the rage. Big Data is firmly installed among the topics available. If you want to go this route, you will need to spend five weeks researching your options. The worthwhile programs are guaranteed to take far longer. As a loose recommendation, Villanova has been making great strides in building their program.
Final note — apologies for the slow and ugly nature of many of these links. It may be an interesting article to investigate why Big Data and great Visualization never want to work in tandum…
Take Five Primers are an article format created by Corsair’s Institute to increase the reader’s comprehension of key concepts by providing learning opportunities that are tailored to the amount of time the reader wishes to engage with a particular subject.
