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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.
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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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