There’s a lot of buzz about Big Data these days. By Big Data, we’re talking Big Mountains of Data. The manipulation of this resource will change the world and do it soon. I hear plenty of lofty goals for the benefit of mankind but destructive ends also seem likely. So what can we expect? I’m here to pass along the short version in plain language.
Tonight we’re treated to speakers from Oracle, CABI, and Narrative Science – a business that grew out of the artificial intelligence labs at the University of Chicago and Northwestern.
Pound for pound, Chicago’s MIT Enterprise Forum is always dense with PhDs and Thought Leaders. I spot a VC in a room dominated by businessmen, academics and MIT alumni. Josh London from Wellter moderates this high-powered session.
Louis Nagode – Oracle
Louis Nagode is a self-proclaimed geek, but he’s world-renowned, with 30 years of business intelligence under his belt. When he talks Big Data, he’s thinking an aggregate of an enormous bulk of worldwide information—ultimately all the knowledge in the world. He says we’re creating data at a phenomenal rate. In the next 2 years we’ll create more data than ever existed before. The key to using it, according to Nagode, is distilling it down to useful information. He breaks it down into four “Vs”:
- Volume—(How do you process it all?)
- Velocity—(How fast does it change?)
- Variety—(How do you make use of it?)
- Value—(How do you make sense of it?)
The big question is this: Can we use Big Data to reduce workload for people, manufacturing, and other altruistic purposes? The next two speakers give concrete answers to that.
Nagode talks about alternatives to databases—alternatives like HDFS, the distribution of data across multiple computers around the globe. That’s data that can be harnessed.
To sift out what we need to know he uses a map-reduce pipeline. Look it up if you want, but it boils down to this: You no longer need a structured query language like SQL. Bottom line, it’s getting a lot easier to use data. Let’s move on and see just how easy this gets:
From Data to Story
Kristian Hammond – Narrative Science
Hammond built the artificial intelligence lab at both the University of Chicago and Northwestern. Now he’s built a Chicago company that takes numbers and symbols and communicates the hidden insights in a more human form. Let me put it more directly: He transforms Big Data into words and narrative. In other words, STORY!
Numbers require expert analysis. Graphs help visualize numbers but we’re still looking at only an 8% penetration. Stories, on the other hand, are highly accessible. They communicate beyond data and tell you things you can’t see. After all, narrative is the way we’ve communicated as long as we’ve been human.
His system produces a short narrative that tells your company the pertinent facts, then gives a summary—A SUMMARY OF WHAT YOU CAN DO THIS WEEK TO MAKE YOUR COMPANY BETTER. We’re not talking about overseas labor knocking this stuff out—no, machines are doing it using artificial intelligence!
Hammond gives an example of a food chain using corporate analytics. The data says that sales of Reuben sandwiches are down. The STORY gives the company easy-to-understand and actionable recommendations, something like this: “Reuben Sandwiches are this week’s weakest menu item with average sales of 136.7 units. Bringing sales up to norm means $7.2MM in added revenue overall. This requires only 6 more sales per store per day.” Now that’s useful information that people can understand and act on.
According to Hammond, people have forgotten the business reasons for data. By telling them the business side in Story, the data becomes immediately useful. As he puts it, “Story is the last mile in Big Data.”
What about education? His system give feedback on an exam with advice on how to improve a student’s performance: “In physics, you need to focus on the Theory of Relativity. Look back to Chapters 5 and 6 of the text.”
How about a sector report for stock analysis? Or a seasonality report for commodity analysis? Why not pull down the Twitter data of all the speakers at a conference and give it out as written analysis? What about a data-driven narrative for media? Turns out that’s a natural. Hey, this could put me out of business!
So how does it work? They analyze nuance and word choice 200 ways plus adjectives and adverbs. They match the client’s written “voice.” They can generate different styles using the same machine. According to Hammond, “Any data, any story, we can do it.”
Now let’s look into using Big Data on a grand scale:
Use it for Good
Roland Dietz – CABI, IERG, Focused Connections Partners
Dietz showed us Big Data in use on the world stage. His organization predicts infestations in plant or animal populations worldwide.
They can show a farmer what might happen to his crop. To do that, they combine data from around the world on climate, soil composition, movement of materials, markets, and many other sources. This model is open source. The data is freely given and freely distributed.
The profit is in what they do with Big Data. As he put it, “We start with tons of information, then identify its significance. That becomes our competitive edge.”
For example, let’s say you track the movement of a pest that destroys coffee plantations. You know the various soils, plant densities, climates, population centers, and topography worldwide. With this, you can predict where the plague will spread.
Some governments don’t want to join CABI, but the group has done good work, even in Korea and Pakistan. When countries see that the organization isn’t political, they accept them. Some are restrictive about what they share because they don’t understand the consequences. But when they find out some of the unexpected benefits of Big Data, they open up.
- Constant Change—The ecosystem is non-linear and always in flux. Using Big Data means doing analysis in real time.
- Analysis—Data without an expert is useless. But just like any science, you come up with a theory based on the data. Then you test it. The scientific method is very much alive and well.
- Opportunities—The biggest opportunities identified so far are in healthcare, world agriculture, education, and evidence-based decision making in business.
- Privacy—This is a huge question that needs to be answered. More and more, people accept constantly observation. But how is the data used? If, for instance, a telecom company has significant insight into YOU, do they keep it proprietary? Can an organization publish information on coffee production in Senegal without permission? I suggested that I’d love to get my hands on coffee pest data to gain an edge trading commodity futures.
- Ethics—Turns out, these speakers aren’t the ones to address this issue. “It’s above my pay grade,” said one. But might not Big Data be used for evil purposes? A member of the audience suggested the specter of ethnic cleansing. Like nuclear power, the possibilities for both altruistic and destructive goals seem endless.
Louis A Nagode—
Oracle – http://www.oracle.com/us/solutions/index.html
Narrative Science – http://www.narrativescience.com/
Focused Connections Partners –http://focusedconnectionspartners.com/
CABI – http://www.cabi.org/ – a not-for-profit international organization that improves lives by solving problems in agriculture and the environment.
IERG – http://www.iergonline.org/ – (International Executive Resource Group) – A not for profit organization of senior business executives from around the world.
Wellter – http://www.wellter.com/ – Enables employees to comparison-shop for healthcare providers.
Emmi Solutions – http://www.emmisolutions.com/ – builds patient empowerment solutions for health organizations that measurably impact outcomes. Their offices are a terrific venue for this event. By the way, they’re still looking for talent. Check out this link: www.EmmiSolutions.com/Careers Looks like a great place to work.
MIT Enterprise Forum, Chicago— http://www.mitefchicago.org/
GO BACK TO PART 1 – WHO’S RUNNING THE ASYLUM
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