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Larry Steinhouse
Larry Steinhouse
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Big Data, Big Business, Big Confusion

We still have a lot to learn about analyzing big data for descriptive, predictive, and prescriptive uses.

Larry Steinhouse, Bicitis Group Inc
Larry Steinhouse, Bicitis Group Inc
I am a frequent attendee of the Wall Street Technology Association's seminars. I find them to be interesting in content and rewarding for all types of networking. In the past year, the seminars have been focused on Big Data and Cyber Security. They often have incredible speakers and the Keynote is always fascinating.

The last seminar on September 19th, was about Big Data. As we get closer to this albatross becoming commonplace, the program hit a number of key points.

This time the Key Speaker was Mark Frost of Booz Allen Hamilton. He described the use of Big Data in a simple term, “Analytics”. I realize that this may fundamental to those reading this article, but it really brought the concept home for me.

Analytics have been used in personal and business applications for as long as there was simple (or complicated) data to reflect upon. Decisions made by this data are sometimes so simple we don’t even realize that this is the application of data. A great example of simple use would be the behavior of my brother. After many years of inviting my brother to everything from birthday parties to weddings, I noticed he was always just about a half hour late. With this data, I now I tell him the event starts a half hour before it really starts. Amazingly, he is always just on time.

So what does this mean to Wall Street, big business and the user communities?

It is simple to understand my brother’s behavior and simple to predict and create a solution, but in big business it is not so simple to predict and create solutions for the consumer.

The challenge of Big Data is what to use and how to apply it. Mark Frost had a great slide in his presentation on a Gartner study. It basically stated that most companies are using data to predict the “what happened” scenario. This is called “descriptive analytics.” This is a scenario where a substantial event occurred and the data is analyzed to find out why it happened.

A great example of this could be the “Black Box” in an airplane. This “black Box” records everything that went on in the cockpit as well as the instruments on the plane. With this recorder, the FAA investigators can determine what went wrong and possibly pinpoint the cause of the crash.

According to the Gartner survey in the slide, 70% of companies are using this data for descriptive analytics. Next it was noted that 16% of companies go to the next step which is “predictive.” To me this is a fantastic use of Big Data. If you can predict or “read the mind” of your customer, you know what they will do. In fact my example of my brother above is predictive. From his behavior, I predict he will be ½ hour late to all invitations.

The uses of predictive data can be incredible to Big Business! If a company like Sears or Macy’s knows that the Tuesday after a holiday is usually slow, they can use that data to prepare for that that day by lessoning staff or having a special sale to bring business into the store. In fact this is the next use of Data that was in the slide. It is labeled “prescriptive” use of data. Clearly my decision to invite my brother a ½ hour earlier is a perfect example of prescriptive use of the data.

I found it very interesting and revealing that this study states that only 3% of Big Business has a prescriptive use for data. Prescriptive use is what big data is all about. Imagine knowing with certainty the buying habits of an individual or individuals. If you know your client and can read his mind, your presentation or marketing can be geared toward his objections or buying triggers. Being in sales for as long as I can remember, this is extremely powerful for my profession. So the big data challenge begins.

Here is the rub, in my example of my brother; I am actually talking about small data. In fact I am talking only one data point. Big Data takes into consideration multiple data points; sometimes even hundreds or thousands or millions of data points. That is the big data dilemma. As companies try to predict the future buying habits of a single customer or even a group of customers there are many things to consider.

Grant Asplund of Blue Coat Systems also spoke at the event. One of the important topics of his presentation was the unpredictability of people. With what you have read so far, by using hundreds or thousands of data points (big data), we should be able to predict the habits and decisions of one or many people. However, people are actually unpredictable. Sometimes people even lie! In fact according to Grant, the biggest lie people make is about their income or weight (reminds me of Match.com, but that’s another story).

Another thing that happens is sometimes people do something “out of the ordinary.” A person going to work every day often takes the same route, however one day they may decide to go left at the corner they have turned right at for years before. Because of all this erroneous information, the big data analyzer has wrong information and creates wrong predictions, bringing the confusion to the analysis of data.

Finally another problem is the relevancy of the data and how it can be applied to marketing or sales. I recall a statement that some say was attributed to Freud; “sometimes a cigar is just a cigar” and whether he said it or not, it makes sense here.

So where is all of this leading?

Well big data is in a childhood state and although it past its infancy state, we still have a lot to learn about analyzing big data for descriptive, predictive, and prescriptive uses. As we watch the evolution of big data analytics, be sure to make note of how your browser and your Facebook, LinkedIn and Twitter accounts react to the types of websites you click on. Watch the ads for that lawn mower you looked at on the Sears website show up in the ads of your Facebook account and every time this happens remember these companies are predicting your behavior and working hard to market to that behavior.

Follow the big data companies and adapt your marketing and sales to the tools that will help decipher the data. If your company hasn’t started a big data analysis, they are missing the upcoming tide. Big data is here to stay so get used to it!

As for me, I have to go prepare invitations for a party this weekend at 3 PM. And of course, my brother’s invitation will be for 2:30.

Larry Steinhouse is a 23 year veteran in Information Technology sales. He is currently in charge of business development for a computer consulting firm called Bicitis Group Inc (BGI). He, along with BGI specialize in the hard to find staffing personal such as Big Data and Cyber Security. He lives with his wife in Hatfield PA and is the author of a book entitled "If I won 25 Million Dollars in the Lottery."

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jacobzyc
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jacobzyc,
User Rank: Apprentice
10/1/2013 | 2:29:22 PM
re: Big Data, Big Business, Big Confusion
Prescriptive use is what big data is all about. So Big Data can also be used in our lives, just like the example of composer's brother. From one's behavior, I can predict what they will do in the future.

Although sometimes people may lie, in big data, I think this will not be a rub. If someone just lie in something for several times, then by large sample, you will find his realistic opinion. If someone lie for every time, it will become his preference and habit. To some extent, that is true.
Greg MacSweeney
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Greg MacSweeney,
User Rank: Apprentice
9/24/2013 | 9:27:52 PM
re: Big Data, Big Business, Big Confusion
Big Datalytics, maybe? or just Big Analytics? LOL
LarryS982
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LarryS982,
User Rank: Apprentice
9/24/2013 | 2:51:02 PM
re: Big Data, Big Business, Big Confusion
Maybe we should coin the phrase "Big Datanalytics" OK maybe not! :)
LarryS982
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LarryS982,
User Rank: Apprentice
9/24/2013 | 2:49:46 PM
re: Big Data, Big Business, Big Confusion
Good Note to add! Thanks for your comment!
LarryS982
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LarryS982,
User Rank: Apprentice
9/24/2013 | 2:48:51 PM
re: Big Data, Big Business, Big Confusion
Greg, I have to agree with you on this one. My guess is that it simpler to justify Big Data applications with sales examples. For me I can easily relate to sales because that's what I do.. The applications for Big Data are numerous including military and cyber attack defense. I took a whimsical and simplistic view to help guide newcomers to the idea. Thanks for the comment! .
Greg MacSweeney
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Greg MacSweeney,
User Rank: Apprentice
9/24/2013 | 11:40:21 AM
re: Big Data, Big Business, Big Confusion
Yes, big data could also be called Big Analytics, since that what it really is. It's nice to have big data, but what firms really want is good analytics....no matter what it is called.
kenjm0154
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kenjm0154,
User Rank: Apprentice
9/23/2013 | 5:21:13 PM
re: Big Data, Big Business, Big Confusion
It should be noted that descriptive and predictive analytics serve the fundamental purpose of reducing risk to the financial institution. Most importantly, this risk includes the loss of revenue due to financial crimes, competitive pressures, regulatory compliance, and IT operations. Each of these risks depends on data (structured and unstructured) and effective data governance. BigData is the foundation of BigAnalytics.
Greg MacSweeney
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Greg MacSweeney,
User Rank: Apprentice
9/23/2013 | 10:02:07 AM
re: Big Data, Big Business, Big Confusion
Almost each "successful" example of big data involves improved marketing or sales. Aren't there examples of big data being used to do other 'successful' things, like finding cures for illnesses or eliminating wasteful spending? I hope so, because if the best technologists can do with a powerful tool like big data is sell more lawnmowers, it would be disappointing.
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