Final Thoughts

There are known knowns; there are things we know that we know. There are known unknowns; that is to say there are things that, we now know we don’t know. But there are also unknown unknowns–there are things we do not know we don’t know.1

—Donald Rumsfeld, while serving as U.S. Secretary of Defense, February 12, 2002

Thanks to forces like mobility, the social web, and the consumerization of information technology (IT), we are living through a permanent data deluge. Enormous data sources are emerging faster than ever. Few intelligent people believe that collectively we’ll generate and consume less data tomorrow than we did yesterday. Big Data is here, and I’m far from the only one who believes that it is changing the world.2

Rather than ignore or fight this inevitability, individuals and organizations of all sizes, types, and industries should embrace it. At some point, just about every employee, department, and organization will face the daunting task of doing more with less. Some will face this challenge sooner than others. And this goes double for the public sector. While not elixirs for fixing the thorny fiscal and budgetary messes in which many agencies find themselves, technology and Big Data are without question part of the solution.

Chapter 2 described the characteristics of Big Data in some detail. Some of those characteristics are in fact limitations of what data can do, no matter how big it gets. That is, data can only tell us so much; even Big Data certainly can’t tell us everything. Rumsfield’s statement at the beginning of this section is as true today as it was more than a decade ago. Overly optimistic folks may believe that data in general—and Big Data specifically—will soon be able to tell us everything. They’re wrong, and they are just as naïve as the skeptics who believe that data can’t tell us anything. The truth is somewhere in between. Most reasonable folks are squarely in the “data will reveal more” camp.

Author and statistician Nate Silver (mentioned in the Introduction) made a similar point on an October 31, 2012 episode of Charlie Rose.3 Silver discussed the inherent limitations of data—specifically, polling data. In other words, despite the remarkable accuracy of his own models and ultimate predictions, Silver knows all too well the limitations of his primary profession. Statisticians never bat 1.000, to use a baseball analogy. Silver sagely told Rose that there will always be unknown unknowns.

And that revelation should in no way preclude you from starting down the Big Data path. The revolution is here, and it’s high time that organizations of all sizes recognize it. As we have seen in this book, baseball teams; retailers; municipalities; car insurance companies; universities like Carnegie Mellon, Columbia, and Princeton;4 and scores of other organizations have already figured this out. Let the tinkering with Big Data begin across the board: public and private sectors, big and small companies, for-profits and nonprofits. Organizations and employees should be asking new and penetrating questions and letting those answers inform new ways of thinking. The uninitiated, the skeptics, and the laggards who refuse to integrate data into their decision-making—and Big Data in particular—will only be left further and further behind.

As Silver puts it, “Data-driven predictions can succeed—and they can fail. It is when we deny our role in the process that the odds of failure rise. Before we demand more of our data, we need to demand more of ourselves.” I couldn’t agree more. I’ve made the following point in my other four books and I’ll end with it here: it’s about the people more than the data and the technology. It all starts with us.

SPREADING THE BIG DATA GOSPEL

Thank you for buying Too Big to Ignore: The Business Case for Big Data. I truly hope you have enjoyed reading it and have learned a great deal in the process. Beyond some level of enjoyment and education (always admirable goals in reading a nonfiction book), I also hope that you can apply your newfound knowledge in your job.

And perhaps you are willing to help me. I am a self-employed author, writer, speaker, and consultant. I’m not independently wealthy, and I don’t have a large marketing machine getting my name out there. My professional livelihood depends in large part on my reputation, coupled with referrals and recommendations from people like you. Collectively, these enable me to make a living.

You can help this book by doing one or more of the following:

I don’t expect to get rich by writing books. I’m not as big as Michael Lewis or Stephen King. Dare to dream, right? I write books for three main reasons. First, although Kindles, Nooks, and iPads are downright cool, I really enjoy holding a physical copy of one of my books in my hands. Creating something physical from scratch just feels good to me. Second, I have something meaningful to say. I like writing, editing, crafting a cover, and everything else that goes into writing books. To paraphrase the title of an album by Geddy Lee, it’s my favorite headache. Finally, I believe that my books will make other good things happen for me.

At the same time, though, producing a quality text takes an enormous amount of time, effort, and money. Every additional copy sold helps make the next one possible.

Thanks again,

Phil

NOTES

1. “News Transcript: DoD News Briefing—Secretary Rumsfeld and Gen. Myers,” February 12, 2002, www.defense.gov/transcripts/transcript.aspx?transcriptid=2636, retrieved December 11, 2012.

2. Hatmaker, Taylor, “5 Ways ‘Big Data’ Is Changing the World,” October 7, 2012, www.entrepreneur.com/article/224582, retrieved December 11, 2012.

3. Watch the episode here: http://tinyurl.com/nate-charlie-rose.

4. Smith, Mike, “Princeton University’s Neuroscience Institute Deploys FileTek StorHouse for Big Data Storage of Vital Laboratory Research and User Information,” September 11, 2012, http://news.yahoo.com/princeton-university-neuroscience-institute-deploys-filetek-storhouse-big-071002005.html, retrieved December 11, 2012.