Transcript Short Presentation Title

Wettbewerbsvorsprung durch
SAP Predictive Analysis
Andreas Forster / Solution Advisor
June 2013
Agenda
• Introduction to Predictive Analysis
• Use Cases, Demo & Customers
• Predictive Applications
• High Performance Applications (on SAP HANA)
• SAP Predictive Analysis
• Architecture and Algorithms
• Questions & Answers
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Definition Predictive Analysis
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Definition Predictive Analysis
Some Data Mining Buzzwords
“
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Data Mining
•
Machine Learning
•
Artificial Intelligence
•
Automatic / Semi-automatic
•
Unknown Correlations, Patterns, Trends
•
Large Data Analysis
Better understand the past to know more about the future.
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Extend your analytics capabilities where you want to be…
Competitive Advantage
Sense & Respond
Predict & Act
Optimization
Predictive
Modeling
Raw
Data
Cleaned
Data
Standard
Reports
Ad Hoc
Reports &
OLAP
What is the best that could
happen?
Generic
Predictive
Analytics
What will happen?
Why did it happen?
What happened?
Analytics Maturity
The key is unlocking data to move decision making from sense & respond to predict & act
© 2013 SAP AG or an SAP affiliate company. All rights reserved.
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SAP’s Predictive Analytics Strategy
Empower the Business
 Extend the Business Intelligence
competency to Advanced
Analytics
 Embed Predictive into Apps and
BI environments
 Lend expertise
In-time Actionable Insights
 In-memory processing
 No data latencies
 Big Data ready
In Context
 Relevant to your business
 Within the context of your
Industry and LOB scenario
 Partner and customer apps
Real-time in-memory predictive and
next generation visualization and modeling
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Agenda
• Introduction to Predictive Analysis
• Use Cases, Demo & Customers
• Predictive Applications
• High Performance Applications (on SAP HANA)
• SAP Predictive Analysis
• Architecture and Algorithms
• Questions & Answers
© 2013 SAP AG or an SAP affiliate company. All rights reserved.
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How Predictive Analytics is Used in Industry
Business and Industry Use Cases where SAP has helped
Healthcare
Predict likelihood of disease to begin early treatment;
identify clinical trial outcomes.
Banking
Identify key behaviors of customers likely to leave
the bank; improve credit risk analysis.
CRM Marketing
Insurance
Identify unusual transactions for fraud prevention.
Rate / Score the risk that is to be insured.
Utilities
Forecast demand and usage for seasonal
operations; provide anticipated resources.
Government
Identify potential leads among existing customers
and intelligently market to them based on individual
preferences and histories
Predict community movement and trends that affect
taxing districts; anticipate revenue.
Retail
Telco
Product suggestions based on past purchases;
inventory planning; selection of store locations based
on demographics.
Forecast demand on system load for capacity
planning and customer scale. Reduce customer
churn. Keep influencer customers.
© 2013 SAP AG or an SAP affiliate company. All rights reserved.
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Demo Time!
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Bigpoint
Gaming Industry - Predictive Game Player Behavior Analysis
5,000 events per
second loaded onto SAP
HANA (not possible
before)
Business Challenges
 Increase conversion rates from free  paying player
 Increase the average revenue per paying player
 Decrease churn – keep paying players playing longer
Technical Challenges
in revenue per year
 Leverage real-time data processing in SAP HANA and classification algorithms with R
integration for SAP HANA to deliver personalized context-relevant offers to players
 Analyze vast amounts of historical and transactional data to forecast player behavior
patterns
Interactive data
Benefits
analysis leading to
improved design
thinking and game
planning
 Real-time insights
 Per player profitability analysis and increased understanding of player behavior
 Increase data volume and processing capabilities to communicate personalized
messages to players
10-30% increase
“”
At Bigpoint in the Battlestar Galactica online game, we have more than 5,000 events in the game per second which we have to load in SAP HANA environment and to
work on it to create an individualized game environment to create offers for them. In this co-innovation project with SAP HANA, using Real Time Offer Management
Bigpoint, we hope to increase revenue by 10-30%.
Claus Wagner, Senior Vice President SAP Technology, Bigpoint
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Mitsui Knowledge Industry
Healthcare – Speed Research & Improve Patient Support
408,000x
faster than traditional
disk-based systems in a
technical PoC
Business Challenges
 Reduce delays and minimize the costs associated with new drug discovery by optimizing
the process for genome analysis
 Improve and speed decision making for hospitals which conduct cancer detection based
on DNA sequence matching
Technical Implementation
216x faster by
reducing genome
analysis from several
days to only 20
minutes making realtime cancer/drug
screening possible
 Leveraged the combination of SAP HANA, R, and Hadoop to store, pre-process,
compute, and analyze huge amounts of data
 Provide access to breadth of predictive analytics libraries
Benefits
 For pharmaceutical companies, provide required new drugs on time and aid identification
of “driver mutation” for new drug targets
 Able to provide a one stop service including genomic data analysis of cancer patients to
support personalized patient therapeutics
“ ”
Our solution is to incorporate SAP HANA along with Hadoop and R to create a single real-time big data platform. With this we have found a way
to shorten the genome analysis time from several days down to only 20 minutes.
Yukihisa Kato, CTO and Director of MITSUI KNOWLEDGE INDUSTRY
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Agenda
• Introduction to Predictive Analysis
• Use Cases, Demo & Customers
• Predictive Applications
• High Performance Applications (on SAP HANA)
• SAP Predictive Analysis
• Architecture and Algorithms
• Questions & Answers
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Predictive Analytics with SAP HANA
Transforming the Future with Insight Today
Unleash the value of Big Data through the
power of SAP HANA
•
•
Employ in-database predictive algorithms
Access 3,500+ open-source algorithms via R
integration for SAP HANA
Intuitively design and visualize complex
predictive models
•
SAP Predictive Analysis software
Bring predictive insight to everyone in the
business
•
•
•
Embed within business applications
Extend into BI and reports
Insight into events instantly delivered to
dashboards, alerts, and mobile devices
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HANA Predictive Applications*
Customer Revenue Performance
Management
Account Intelligence
Predictive Customer Segmentation
*: Predictive seamlessly embedded in applications
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SAP Predictive Analysis
Intuitively design complex predictive models
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Read and write from data stored in SAP HANA, Universes, IQ, and other sources
Drag-and-drop visual interface for data selection, preparation, and processing
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SAP Predictive Analysis
Data Visualization and
Sharing
1. Visualize the model for
better understanding
2. Store the model and result
back to SAP HANA
3. Share results via PMML
and with other BI client
tools
Step1
Data Loading
Step 4
Data
Visualization and
Sharing
Data Processing
1. Define the model via clustering ,
classification, association, time
series, etc.
2. Run the model
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Data Loading
1. Understand the business and
identify issues
2. Load the SAP and non-SAP data
into SAP HANA or other source
Step 2
Data Preparation
Step 3
Data Processing
Data Preparation
1. Visualize and examine the
data
2. Sample, filter, merge,
append, apply formulas
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SAP Predictive Analysis
Visualize, discover, and share hidden insights


Advanced visualization designed where you’d expect it – natively from within the modelling tool
Share insights via PMML and with other BI client tools
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Agenda
• Introduction to Predictive Analysis
• Use Cases, Demo & Customers
• Predictive Applications
• High Performance Applications (on SAP HANA)
• SAP Predictive Analysis
• Architecture and Algorithms
• Questions & Answers
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Options to use SAP Predictive Analysis
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Data Sources for SAP Predicitve Analysis
Access & Merge
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SAP HANA In-Memory Predictive Analytics
Combine the depth and power of in-memory analytics within SAP HANA with the
breadth of R to support a variety of advanced analytic and predictive scenarios
Predictive Analysis Library (PAL)
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Native predictive algorithms
In-database processing for powerful and fast results
Quicker implementations
Support for clustering, classification, association, time series etc…
R Integration for SAP HANA
 Enables the use of the R open source environment (> 3,500
packages) in the context of the HANA in-memory database
 R integration enabled via high performing parallelized connection
 R script is embedded within SAP HANA SQL Script
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SAP HANA Predictive Ecosystem
SAP Predictive
Analysis
SAP and Custom
Applications
Business
Intelligence
Clients
SAP HANA Platform
Predictive Analysis
Library (PAL)
SAP HANA Studio
R Integration for
SAP HANA
R
Data Pre-Processing and Loading
SAP Data Services, Information Composer, SLT, DXC, Hadoop
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SAP HANA In-Memory Predictive Analytics
Predictive Analysis Library (PAL) - Algorithms Supported
Association Analysis
 Apriori
 Apriori Lite
Cluster Analysis
 K-Means
 Kohonen Self Organized Maps
Classification Analysis
 C4.5 Decision Tree Analysis
 CHAID Decision Tree Analysis
 K Nearest Neighbour
 Multiple Linear Regression
 Polynomial Regression
 Exponential Regression
 Bi-Variate Geometric Regression
 Bi-Variate Logarithmic Regression
 Logistic Regression
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Time Series Analysis
 Single Exponential Smoothing
 Double Exponential Smoothing
 Triple Exponential Smoothing
Outlier Detection
 Inter-Quartile Range Test (Tukey’s Test)
 Variance Test
 Anomaly Detection
Data Preparation
 Sampling
 Binning
 Scaling
Other
 ABC Classification
 Weighted Scores Table
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R Integration for SAP HANA
What is R?
R is a software environment for statistical computing and
graphics
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Open Source statistical programming language
Over 3,500 add-on packages; ability to write your own functions
Widely used for a variety of statistical methods
More algorithms and packages than SAS + SPSS + Statistica
Who’s using it?
 Growing number of data analysts in industry, government, consulting, and
academia
 Cross-industry use: high-tech, retail, manufacturing, CPG, financial
services , banking, telecom, etc.
Why do they use it?
 Free, comprehensive, and many learn it at college/university
 Offers rich library of statistical and graphical packages
© 2013 SAP AG or an SAP affiliate company. All rights reserved.
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The Forrester Wave™
Big Data Predictive Analytics Solutions, Q1 2013
A leader in predictive
 “SAP is a newcomer to big data
predictive analytics but is a Leader due to
a strong architecture and strategy.”
Comprehensive and holistic
approach to “Big Data”
 “SAP also differentiates by putting its
SAP HANA in-memory appliance at the
center of its offering, including an indatabase predictive analytics library
(PAL), and offering a modeling tool that
looks a lot like SAS Enterprise Miner and
IBM SPSS Modeler.”
The Forrester Wave™ is copyrighted by Forrester Research, Inc. Forrester and Forrester Wave™ are trademarks of Forrester Research, Inc. The Forrester Wave™ is a graphical representation of Forrester's call on a
market and is plotted using a detailed spreadsheet with exposed scores, weightings, and comments. Forrester does not endorse any vendor, product, or service depicted in the Forrester Wave. Information is based on best
available resources. Opinions reflect judgment at the time and are subject to change.”
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Agenda
• Introduction to Predictive Analysis
• Use Cases, Demo & Customers
• Predictive Applications
• High Performance Applications (on SAP HANA)
• SAP Predictive Analysis
• Architecture and Algorithms
• Questions & Answers
© 2013 SAP AG or an SAP affiliate company. All rights reserved.
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Predictive Analysis Quick Start Services
Planning Assessment for Predictive
Analysis
1
Implementation of Predictive
Analysis Using HANA
2
Scope:
Scope:
Assess goals for predictive Analysis and current
state
 Identify what data will be needed
 Identify user groups and enablement plan
 Roadmap to predictive Analysis maturity
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Duration: ~2 days
Duration: ~20 days
Resources
Resources
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
Decision Scientist
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



© 2013 SAP AG or an SAP affiliate company. All rights reserved.
In addition to PA Quick Start, data integration with
a HANA (or EDW) data source
Data model in HANA to support predictive model
Leverage HANA for faster performance
Decision Scientist
PA Tech Architect
Data Architect
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Zusammenfassung – 5 Punkte zum Mitnehmen
1. SAP macht Predictive Analysis!
2. Mit SAP Predictive Analysis können Fachanwender ohne
grossen Schulungsaufwand Data Mining betreiben.
3. Mit SAP HANA geht es noch detaillierter und schneller.
4. Business Applikationen bringen Predictive direkt in die Prozesse.
5. Möglichkeit der gemeinsamen Entwicklung von
kundenspezifischen Predictive Applikationen.
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Thank you
Contact information:
Andreas Forster
Solution Advisor
SAP Schweiz
+41 797 01 8944, [email protected]
© 2013 SAP AG or an SAP affiliate company. All rights reserved.