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Big Data What does it mean ? How do we mine it?. John Johansen October 2013 [email protected]. Session Objective. Who saw that coming! Our organizations’ data is increasingly capable of helping us anticipate and plan for the unexpected. - PowerPoint PPT Presentation
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Big DataWhat does it mean? How do we mine it?
John JohansenOctober [email protected]
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Session Objective
Who saw that coming!• Our organizations’ data is increasingly capable of helping us anticipate and plan for
the unexpected. – Powerful tools are emerging to help identify patterns and make predictions of potential risks and
opportunities.– These predictive analytics will allow companies to focus on the real trouble spots and develop the right
conclusions.
• This session will explore and demonstrate these tools while identifying potential applications and solutions in our day-to-day jobs.
• At the conclusion of the session participants will understand– The role that analytics can play in supporting your organizational objectives.– How these tools can identify elevated risk and help plan effective strategies to maximize opportunities.
Who saw that coming? You did!
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Agenda
• Big Data Explained
• Why Are These Solutions Emerging Now ?
• Some Common and Not-so Common Applications in our Businesses
• The Steps in the Mining Process
• A Real Live Demo of a Mining Process
• Questions
• Wrap - Up
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But first… a promise…
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But first… a promise…
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But first… a promise…
No plunge !
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Big Data Explained
Volume
Velocity
RF Tagging
Healthcare Monitoring
Unstructured Data
Sensor Data
Real Time Data
> Peta? Zetta
Voice of the Customer Text Analysis
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Four Emitters Connected to the Internet of Things
• Cows & Crops
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Transactions, Interactions & Observations
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Big Data in the Gartner Hype Cycle
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There are less scientific hype indicators
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Why Now?
• Chances are, the tools you need are the tools you have.*
• At long last, the data that you need is the data that you have.
• The processing power that you need is the processing power that you have.*
* And if you don’t already have them, they are readily available with very reasonable ROI
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Four Emitters Connected to the Internet of Things
• Cows & Crops
• Christmas Trees
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Data is Increasingly a Differentiator
Production Reporting
Interactive Dashboards
Data Discovery
Predictive AnalyticsOperational Analytics
Diffe
rent
iatio
n
Sophistication
High
Low
Low High
Predictive Analytics
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Potential Challenges
“Prediction is very difficult…
Niels Bohr
Casey Stengel
President Bill Clinton
Especially if it’s about the future.”
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Predictive Analytic Solutions
• We see these solutions as a class of software tools that will look through large sets of data to uncover subtle patterns in data, then use those patterns to predict the behavior of a new set of data.
• The impact these solutions are having at companies are generally in the areas of:– Improving the profitability of existing clients by identifying high probability
cross-selling activities.– Improving the effectiveness of direct marketing programs through more
focused, higher likelihood of success programs.– Identifying fraud.– Identifying likely candidates for churn either in the customer-base or in the
channel.– Modeling customer reactions to price or term changes.
Organizations Embrace Analytics Differently
Killer Applications
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What are the steps?
• As with any other solutions, we suggest starting at the end: Outlining specifically what we are hoping to achieve.
• Next we need to establish at least two sets of data from our existing historical data. One will help us Train the model, the other will be a Test set that will allow us to validate that in fact the model that we create is valid.
• Once we’re sure we’ve got a model that establishes the right relationships, we can run our source data through our model and get our predictions.
• Analyze, Rinse. Repeat.
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Four Emitters Connected to the Internet of Things
• Cows & Crops
• Christmas Trees
• Pill Bottles
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Demonstrating the Power
• We’ve arranged for a quick demo of the Microsoft tools.
– Churn Prediction
– Claim Amount
– Cross Selling
• It’s interesting to note, that this demonstration is running on a simple server, using software tools that are included, free, with Microsoft SQLServer.
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Demonstration – Predicting Churn
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Demonstration – Claim Cost
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Demonstration – Cross Selling
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Four Emitters Connected to the Internet of Things
• Cows & Crops
• Christmas Trees
• Pill Bottles
• Diapers
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Questions?
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In conclusion…
• Big Data Explained
• Why Are These Solutions Emerging Now ?
• Some Common and Not-so Common Applications in our Businesses
• The Steps in the Mining Process
• A Real Live Demo of a Mining Process
• Questions
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In conclusion…
“I figure lots of predictions is best. People will forget the ones I get
wrong and marvel over the rest.”
Alan Cox
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Contact
John JohansenPartner
Agile Technologies, LLCOne Easton Oval, Suite 388
Columbus, Ohio 43219
www.agiletech.com