When I first saw the Internet in 1993, I was dumbstruck by the obvious wonderfulness of its potential.
I had been in sales and marketing for 15 years and was knowledgeable about networks. I also understood humans’ overwhelming need to communicate and figured this was sure to be, well, wonderful.
I felt the same way about big data as soon as I heard IBM’s Jeff Jonas present at the eMetrics Marketing Optimization Summit last October in New York. But I’ve been much less able to explain why until I added a new word to my vocabulary.
Big Data Defined
In common parlance, big data has arrived due to:
- Volume. We have more data than ever imagined.
- Variety. Who knew we would be tracking and collecting mouse movements on websites or tire pressure and temperature?
- Velocity. Near real-time monitoring is essential when operating in a social media world.
In a nutshell, big data is more data than we are accustomed to. Get used to not being able to get used to how much data you have. It’ll never stop.
Big Data Promise
The breakthrough was a technical one but the popular consensus is that the more data you have, the more knowledge you can glean from it. It’s a bit like the old joke about the optimistic boy and the room full of horse manure…
(Side bar) Worried that their son was too optimistic, the parents of a little boy took him to a psychiatrist. Trying to dampen the boy’s spirits, the psychiatrist showed him into a room piled high with nothing but horse manure. Yet instead of displaying distaste, the little boy clambered to the top of the pile and began digging.
“What do you think you’re doing?” the psychiatrist asked.
“With all this manure,” the little boy replied, beaming, “there must be a pony in here somewhere!” (/side bar)
Big Data Broken Promise
While this distributed processing technology lets us tackle larger and larger datasets, it doesn’t do a thing to help us with analysis.
We’re still digging through the same old manure in the same old way – but with a bigger shovel.
Big Data Hope
Jeff Jonas’ claim is that we can build systems where “data finds data.”
The idea, and the word for it, is consilience.
Merriam Webster defines consilience as, “the linking together of principles from different disciplines especially when forming a comprehensive theory.”
“In science and history, consilience (also convergence of evidence or concordance of evidence) refers to the principle that evidence from independent, unrelated sources can ‘converge’ to strong conclusions. That is, when multiple sources of evidence are in agreement, the conclusion can be very strong even when none of the individual sources of evidence are very strong on their own.”
In chapter 7 of the book “Beautiful Data: The Stories Behind Elegant Data Solutions,” Jeff Jonas wrote:
“Next-generation ‘Smart’ information management systems will not rely on users dreaming up smart questions to ask computers; rather, they will automatically determine if new observations reveal something of sufficient interest to warrant some reaction, e.g., sending an automatic notification to a user or a system about an opportunity or risk.
… When the ‘data can find the data,’ there exists an opportunity for the insight to find the user.”
So I still live in hope that big data, beyond being the latest catch phrase for all marketing mavens (“Spicy Chicken McBites – Now with BIG DATA!”), will evolve from merely being able to manage large datasets to systems that can participate in that uniquely human act of discovery.
The day will come when the system pops up an alert that says, “Gee, that’s funny…”
Marketers need to know what’s in their data and trim out the filler to provide continuous, data-driven ROI for their brands.
A new starter in Team SaleCycle recently asked me the following question… “Wouldn't they just come back anyway?”
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