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PRACTICAL APPROACHES TO INTERACTIVE

DATA DISCOVERY & PREDICTIVE ANALYTICS

WAYNE THOMPSON, CHIEF DATA SCIENTIST

TAPAN PATEL, PRODUCT MARKETING MANAGER

JANUARY 2016

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APPROACHABLE ANALYTICS

Unlimited Data

• Embrace the potential of using all or

relevant data

Speed to Insights

• Try things fast, prototype & refine, &

ask different questions

Democratized Analytics• Empower more people (e.g. citizen

data scientist, business analysts)

 Approachable Analytics

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APPROACHABLE

ANALYTICSBarriers to the adoption of analytics

Scarcity of analytical skillsThe need to grow analytical talent from within

Disjointed, inefficient workflowHow can you fail fast & learn to refine quickly 

Tools that aren’t right for the jobLearning curve to create, share and collaborat

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APPROACHABLE

ANALYTICSBI AND ANALYTICS CONTINUUM

Descriptive•

What is

happening?

•

Report/Monitor

Results

Predictive•

What will

happen?

•

Identify

Outcomes

Diagnostic•

Why did it

happen?

•

Understand the

context

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APPROACHABLE

ANALYTICSINTERACTIVE DATA DISCOVERY AND ANALYTI

• Data exploration and disc• Distribution and summary

• Post-model visualization a

• Build prediction and class

• Refine candidate models

• Compare models and gen

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APPROACHABLE

ANALYTICSIN-MEMORY ANALYTICS

HADOOP or DW APPLICATIONS

Visual Analytics

Visual Statistics

ERP

SCM

CRM

Images

Audio

and Video

Machine

Logs

Text

f Web and

Social

In-memory

Statistics

SAS ®  IN-MEMORY

SAS ®  IN-MEMORY

SAS ®  IN-MEMORY

SAS ®  IN-MEMORY

SAS ®  IN-MEMORY

SAS ®  LASR ANALYTIC

SERVER

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SAS®

VISUAL

STATISTICSEXPLORE DATA AND MODELING RESULTS

• Discover relationships between variables amodel building process

• Derive models directly from correlation matrice

plots, box plots and heat maps

• Understand individual variable’s level of inf

all models• Explore results from the modeling process

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SAS®

VISUAL

STATISTICSMODELING TECHNIQUES

• Predictive Techniques

• Linear Regression

• Logistic Regression

• Generalized Linear Model

• Classification Trees

• Descriptive Techniques

• Clustering

• Group-By Processing

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PRODUCT DEMONSTRATION

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DIRECTPAY

BUSINESS ISSUE

• Determine what debt to buy and how to best collect it

• Estimates of potential debt portfolios for purchase were

time-consuming

• Understand customer behavior to accelerate payments

and increase revenue

SOLUTION

• SAS Visual Analytics and SAS Visual StatisticsRESULTS

• Complete view of its customers and can make

individualized decisions for the debt-collection process.

• Manage risks at debtor and client level in order to be

profitable.

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KEY BENEFITS

End-to-end capabilitiesSmart data discovery, interactive reporting & analytics

Built-in interactive analyticsExplore data and generate models in a common environment

Scalability & governanceSmall to large – users, data, workloads, etc.

1

2

3

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SAS®

VISUAL STATISTICS - TRY IT YOURSELF!

FREE14-Day Trial (Your Data

Coming Soon

FREEInteractive Demo

Trial

www.sas.com/visualstatistics

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SAS®

DATA LOADER FOR HADOOP  – DOWNLOAD AND TRY IT Y

www.sas.com/dataloader 

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