SAP Big Data Forum 2013 C4 Alexis Fournier - SAP

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SAP Big Data Forum 2013 C4 Alexis Fournier - SAP

  1. 1. SAP Predictive Analysis Alexis Fouquier – D&T EMEA Alexis.Fouquier@sap.com
  2. 2. Agenda  The Predictive Analytics Landscape  Predictive Analytics with SAP HANA SAP Predictive Analysis Customers Benefit from Predictive Analytics Q&A © 2013 SAP AG. All rights reserved. Internal 2
  3. 3. Agenda  The Predictive Analytics Landscape  Predictive Analytics with SAP HANA SAP Predictive Analysis Customers Benefit from Predictive Analytics Q&A © 2013 SAP AG. All rights reserved. Internal 3
  4. 4. Everything is accelerating Real-time is standard for the digital economy mail Business needs express fax e-mail Document transfer 100 ms Reduce processing time 20 min 20 ms Algorithmic trading 30 sec Airline operations CIO strategy 8 hr Zero Latency 10 sec 1 day 5 min 1 day Served the same day Supply chain updates 1 min 1 week Phone activation 0.5 hour 5 days Refresh data warehouse 2 hrs. 4 weeks © 2013 SAP AG. All rights reserved. Track financial position 15 min 3 days Typical Business SLAs Call center inquiries Trade settlement 1 day 106 105 104 Build-to-order PC 103 100 10 1 0 Seconds Internal 4
  5. 5. Everything become big © 2013 SAP AG. All rights reserved. 5
  6. 6. Big data matters Transformational business value from data Velocity Drive Better Profit Margins Instant Messages CRM Data Mobile Business Value Customer Things Demand Sales Order Transactions Operational Efficiencies New Strategies and Business Models Planning Volume © 2013 SAP AG. All rights reserved. Opportunities Inventory Variety Internal 6
  7. 7. Move from reporting to proactive decision Competitive Advantage Sense & Respond Predict & Act Optimization Predictive Modeling What is the best that could happen? Generic Predictive Analytics Ad Hoc Reports & OLAP Raw Data Cleaned Data What will happen? Standard Reports 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. All rights reserved. Internal 7
  8. 8. 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. All rights reserved. Internal 8
  9. 9. Forrester Wave: Big Data Predictive Analytics • SAP is a leader in the 2013 Forrester Big Data Predictive Analytics wave • SAP went from not appearing on the wave to leader within one year • SAP’s in-memory predictive analytics approach is unparalleled and unique among vendors • SAP’s vision and roadmap for predictive analytics is well-received by analysts © 2013 SAP AG. All rights reserved. Internal 9
  10. 10. Agenda The Predictive Analytics Landscape Predictive Analytics with SAP HANA SAP Predictive Analysis Customers Benefit from Predictive Analytics Q&A © 2013 SAP AG. All rights reserved. Internal 10
  11. 11. 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. All rights reserved. Internal 11
  12. 12. 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. All rights reserved. Internal 12
  13. 13. Agenda The Predictive Analytics Landscape Predictive Analytics with SAP HANA SAP Predictive Analysis Customers Benefit from Predictive Analytics Q&A © 2013 SAP AG. All rights reserved. Internal 13
  14. 14. SAP Predictive Analysis is… A complete data discovery, visualization, and predictive analytics solution designed to extend your current analytics capability and skillset. SAP Predictive Analysis Data Discovery © 2013 SAP AG. All rights reserved. Rich Visualizations Predictive Analytics Internal 14
  15. 15. Data Discovery, Predictive, and Visual Suite for Big Data Explorer Mobile Explorer Dataset Information Space Lumira HANA © 2013 SAP AG. All rights reserved. StreamWork Visualizations Exploration Views Predictive Analysis SQL UNV Internal 15
  16. 16. SAP Predictive Analytics – Real Business Value Faster • Real-time answers • Access to disparate enterprise data • Allows discovery to prediction to results in minutes Easier • Intuitive business design • Designed for more users for answering more questions with less effort • Same experience and interface as other BOBJ products Transforming • • • Enables deep insight to immediate action Proactive and forwardlooking visibility into the business Allows for greater competitive advantage User powered, IT approved © 2013 SAP AG. All rights reserved. Internal 16
  17. 17. 3 Simple Steps to SAP Predictive Analytics 1 Load Your Data From Any Source 2 Discover, Enrich, & Visualize Results 3 Apply Predictive Models & Publish 100101 011010 100101 © 2013 SAP AG. All rights reserved. Internal 17
  18. 18. Designed for business users data scientists To extend your analytics capabilities Optimized for real time and big data Easy to use with a short learning curve © 2013 SAP AG. All rights reserved. Internal 18
  19. 19. Agenda The Predictive Analytics Landscape Predictive Analytics with SAP HANA SAP Predictive Analysis Customers Benefit from Predictive Analytics Q&A © 2013 SAP AG. All rights reserved. Internal 19
  20. 20. Some Predictive Use Cases by Industry Customer churn, network optimization, cross/up selling, customer retention, network fraud Telecommunications detection Banking/Finance Credit risk management, antimoney laundering, fraudulent card usage detection Forecasting, inventory planning, cross/up selling, customer segmentation, market basket analysis Customer profitability, fraudulent claims detection and prevention Insurance Automotive Demand forecasting, service parts optimization, production maintenance Retail Public Sector Healthcare Logistics optimization, fraud prevention Health management, fraud prevention © 2013 SAP AG. All rights reserved. Price optimization, assortment Manufacturing/Wholesale planning, forecasting Predictive asset maintenance, market and credit risks Utilities Internal 20
  21. 21. Make Customer Centricity your biggest advantage 1 Better segment customers for growth campaigns Customers Leverage your Big data for real-time Predictive Analysis and modeling Target customer with real-time personalized promotions Analyze and understand customer sentiments to serve them better Get 360° Insight into Your Customer SAP BusinessObjects BI Suite on HANA SAP Predictive Analysis
  22. 22. Efficiency and autonomy Trend Analysis Stock optimization Planning and hiring
  23. 23. Optimization and Customer satisfaction Accruals optimization Warranties Customer satisfaction
  24. 24. Valorization and optimization Fleet Management Valorization Cash optimization Fleet Management
  25. 25. Fraud Management Insurances Reduce fraud by 750M€ over 3 years Increase profitability New fraudulent behaviors
  26. 26. Increase productivity Explorations Increase production by 1 Billion $ per year Reduce production costs Decrease maintenance costs
  27. 27. Reduce criminality Polices Reduce criminality Dynamic police force allocation Reduce cost
  28. 28. Thank you

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