Wettbewerbsvorsprung durch SAP Predictive Analysis Andreas Forster Solution

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 © 2013 SAP AG or an SAP affiliate company. All rights reserved. 2

Definition Predictive Analysis © 2013 SAP AG or an SAP affiliate company. All rights

Definition Predictive Analysis Some Data Mining Buzzwords “ • 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. © 2013 SAP AG or an SAP affiliate company. All rights reserved. 4

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. 5

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 © 2013 SAP AG or an SAP affiliate company. All rights reserved. 6

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. 7

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 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. 8

Demo Time! © 2013 SAP AG or an SAP affiliate company. All rights reserved.

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 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 in “” 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 © 2013 SAP AG or an SAP affiliate company. All rights reserved. 10

Mitsui Knowledge Industry Healthcare – Speed Research & Improve Patient Support 408, 000 x faster than traditional disk-based systems in a technical Po. C 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 216 x 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 © 2013 SAP AG or an SAP affiliate company. All rights reserved. 11

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. 12

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 © 2013 SAP AG or an SAP affiliate company. All rights reserved. 13

HANA Predictive Applications* Customer Revenue Performance Management Account Intelligence Predictive Customer Segmentation *: Predictive seamlessly embedded in applications © 2013 SAP AG or an SAP affiliate company. All rights reserved. 14

SAP Predictive Analysis Intuitively design complex predictive models Read and write from data stored in SAP HANA, Universes, IQ, and other sources n Drag-and-drop visual interface for data selection, preparation, and processing n © 2013 SAP AG or an SAP affiliate company. All rights reserved. 15

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 Step 1 Data Loading 1. Understand the business and identify issues 2. Load the SAP and non-SAP data into SAP HANA or other source Data Loading Step 4 Step 2 Data Visualization and Sharing Data Processing 1. Define the model via clustering , classification, association, time series, etc. 2. Run the model © 2013 SAP AG or an SAP affiliate company. All rights reserved. Data Preparation Step 3 Data Processing Data Preparation 1. Visualize and examine the data 2. Sample, filter, merge, append, apply formulas 16

SAP Predictive Analysis Visualize, discover, and share hidden insights Advanced visualization designed where you’d expect it – natively from within the modelling tool n Share insights via PMML and with other BI client tools n © 2013 SAP AG or an SAP affiliate company. All rights reserved. 17

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. 18

Options to use SAP Predictive Analysis © 2013 SAP AG or an SAP affiliate

Data Sources for SAP Predicitve Analysis Access & Merge © 2013 SAP AG or

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) § § 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 © 2013 SAP AG or an SAP affiliate company. All rights reserved. 21

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 © 2013 SAP AG or an SAP affiliate company. All rights reserved. 22

SAP HANA In-Memory Predictive Analytics Predictive Analysis Library (PAL) - Algorithms Supported Association Analysis § Apriori Lite Cluster Analysis § K-Means § Kohonen Self Organized Maps Classification Analysis § C 4. 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 © 2013 SAP AG or an SAP affiliate company. All rights reserved. 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 23

R Integration for SAP HANA What is R? R is a software environment for statistical computing and graphics 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. 24

The Forrester Wave™ Big Data Predictive Analytics Solutions, Q 1 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. ” © 2013 SAP AG or an SAP affiliate company. All rights reserved. 25

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. 26

Predictive Analysis Quick Start Services Planning Assessment for Predictive Analysis 1 Implementation of Predictive Analysis Using HANA 2 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 § Duration: ~2 days Duration: ~20 days Resources § Decision Scientist © 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 § 27

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. © 2013 SAP AG or an SAP affiliate company. All rights reserved. 28