Big Data & Predictive Analytics

Michael Stencl

Agenda Big Data Predictive Analytics

So what?

Big data definition

Source: Big data analytics By Philip Russom TDWI best practices report , 4th Quarter 2011

Big data definition

Source: Big data analytics By Philip Russom TDWI best practices report , 4th Quarter 2011

What’s the approximate total data volume that your organization manages only for analytics,both today and in three years?

Source: Big data analytics By Philip Russom TDWI best practices report , 4th Quarter 2011

What’s the approximate total data volume that your organization manages only for analytics, both today and in three years?

Source: Big data analytics By Philip Russom TDWI best practices report , 4th Quarter 2011

Paul Bachteal, SAS Technology Strategies for Big Data Analytics

What is behind Predictive analytics is the branch of data mining concerned

with the prediction of future probabilities and trends.

What the Predictive analytics is

Business intelligence technology

Produces a predictive model which has, in turn, been trained over your data

Learning from the experience of your organization

Uses data that has the company reported

What is good for

Behavioral Segmentation, Loyalty analysis and Revenue prediction are just the beginning

Bring to customer highly automated advanced analytics workflow

ApplicationsChurn Rate

Product Portfolio MixBad Debt Reduction

Fraud DetectionCustomer Life Cycle

Cost of Sales and Marketing

MethodsRegression

ClassificationAnomaly Detection

ClusteringAssociation

Feature Selection and Extraction

ConferenceJames Taylor

Decision Management SolutionAzhar IqbalWells Fargo Securities

Eric Siegel, Ph.D.

Pre

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tics World

Erick BrethenouxIBM Business Analytics

Kelley Blue Book

Kevin B. PrattZZAlpha LTD.

Piyanka JainAryng Inc.

Paul BachtealSAS

5 Myths of PA Is Predictive Analytics (PA) new?? Is it a crystal ball?? Is it perfect?? Press a button solution?? Does it always work??

Piyanka Jain, Aryng In

When was the first application of Predictive Analytics?

A. 1960’s – Advent of computing powerB. 1930’s – Wall street crashC. 19th century – Birth of science as profession D. Before 15th century

What Business people expect?

BADIR

Keep it simple

You think its complicated... Hmm

Did you ever dropped food on a floor?

Do you eat it???

Predictive Analytics in Cloud 5 areas of opportunity

Pre-packaged cloud based solutions Cloud based predictive analytics for SaaS Cloud based Predictive analytics for on premise Predictive modeling with data in the cloud Elastic compute power

James Taylor, Decision Management Solutions

Why?Predictive Analytics

Automatically discover patterns in dataPredict trends or likely future behaviorIdentify population segments

Cloud ComputingComputing resources delivered as a serviceMulti-tenancy and shared resourcesUsage pricing and location transparency

Commonly Used Methods

other possible methods Clustering (K-means), PCA Factor Analysis, Time Series, Survival Analytics Neural Networks, Genetic Regression and Algorithm

Logistic Regression

DecisionTree

Linear Regression

Where to compute it? 2 groups of software

Framework based SW R Matlab

Solution based SW Weka RapidMiner KNIME Mahout

Thank You!