SAP HANA - The Foundation of Real Time, Now on the AWS Cloud Computing Platform

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The future holds many transformational opportunities. Capitalize on the new technology frontier and realize value previously unattainable with SAP HANA. Learn how SAP and AWS are collaborating to …

The future holds many transformational opportunities. Capitalize on the new technology frontier and realize value previously unattainable with SAP HANA. Learn how SAP and AWS are collaborating to empower businesses, developers, startups and even sports fans to take advantage real time computing in the cloud.

SAP and AWS experts will outline:
• How do SAP and AWS align to support your cloud strategy, large or small?
• What is SAP HANA and how does it enable you to run your business in real-time?
• Use cases for developers and enterprise; and capabilities including analytics, business processes, sentiment data processing, and predictive.
• How to get immediate value by deploying SAP HANA on the AWS cloud computing platform.
• Best practices and reference guides to help you.
• Customer success stories, including the Women’s Tennis Association (WTA).

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  • 1. © 2014 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc. SAP HANA - The Foundation of Real Time Now on the AWS cloud computing platform David Payne, Joe Binkley, Steven Jones July, 2014
  • 2. Anyone for tennis?
  • 3. Anyone for data?
  • 4. 4© 2014 SAP AG or an SAP affiliate company. All rights reserved.
  • 5. 6 Serve Direction PETKOVICCIBULKOVA Available Imagery Return Contact Point Rally Hit Point Shot Placement
  • 6. 7© 2014 SAP AG or an SAP affiliate company. All rights reserved. 7
  • 7. 8© 2014 SAP AG or an SAP affiliate company. All rights reserved. 8
  • 8. 9© 2014 SAP AG or an SAP affiliate company. All rights reserved.
  • 9. 10© 2014 SAP AG or an SAP affiliate company. All rights reserved.
  • 10. A key enabler to the global economy for over 40 years, SAP is uniquely positioned to help the world run better At the global level Helping customers optimize resources and protect the environment At the business level Helping companies harness data to stay ahead of change and innovate for growth At the personal level Helping people have a greater voice and live better lives by personalizing engagement SAP mobile solutions reach 97% of the world’s mobile subscribers via text messaging. SAP customers represent 98%of the top 100 most valued brands in the world. 74% of the world’s transaction revenue touches an SAP system.
  • 11. Profound changes are leading to an unprecedented empowerment of people everywhere We need to rethink the future. Run business in real time 3 Optimize resources 1 An emerging middle class growing to 5 billion will strain already diminishing resources More mobile devices than people will require fresh thinking designed for an “always-on” world Use Big Data to your advantage 2 Data doubling every 18 months will create new opportunities and risks for value creation 15 billion Web- enabled devices by 2013 will create a universe of intelligence everywhere 1 billion people in social networks will rewire business and personal boundaries
  • 12. Imagine a new world of real-time engagement where innovation in technology can.. … While improving the lives of people everywhere Power of the individual Improvement in people’s lives Help companies stay ahead of change and innovate for growth … Future of Business Redefinition of business models A better-run world smarter, faster, simpler
  • 13. © 2013 SAP AG or an SAP affiliate company. All rights reserved. 14Public SAP Strategy SAP HANA Cloud Platform Application Services | Development | Integration | Database and Analytics | Foundation BUSINESS NETWORK BUSINESS TO BUSINESS COLLABORATION SOCIAL PEOPLE TO PEOPLE COLLABORATION HR SALES, SERVICE, MARKETING FINANCE PROCUREMENT PARTNER/ ISV APPS PUBLIC CLOUD APPLICATIONS SAP BUSINESS SUITE BW MANAGED CLOUD SAP & PARTNERS HANA MARKETPLACE
  • 14. At the heart of its innovation is SAP HANA, a completely re-imagined platform designed for real-time business 10,000x Faster helps you process massive amounts of data, and deliver information at unprecedented speeds Entirely New Possibilities enables you to create previously unimaginable applications, and to rethink and envision new ways to run your business Dramatically Simplified IT Deployable as an on-premise appliance or in the cloud, SAP HANA dramatically simplifies complex and expensive IT architectures Completely Open Platform as an open, adaptable, and extensible platform SAP HANA a revolutionary in-memory platform
  • 15. Joe Binkley Technical Lead, Experience SAP HANA
  • 16. Real-time Business Scenario Real-time bonus calculations for consumers Sales Customer Service Customer overdue credit calculation by product areas Finance and Operations Iterative period end closing with new posting into accounts constantly Manufacturing New ATP strategies; MRP run for individual ATP check/instant re-planning IMPACT ON BUSINESS Slow Response Times | Usability Challenges | Lack Of Adaptability IMPACT ON IT High Latency | Complexity | High Cost of Solutions Transactional Datastore Data Warehouse Sensors Data Mobile Data Archives Social & Text Geo-Spatial Location Intelligence Order Processing Operational Reporting Real-time Risk & Fraud Trend Analysis Sentiment Analytics Predictive Analytics Pattern Recognition Analyze ETL Staging Collect Clean-Data Quality Transact Aggregate Summarize Communicate Monitor Predict Planning 0 1 Information Processing is at a critical inflection point Point optimization is not enough to meet the new frontiers of real-time business
  • 17. DEEP Complex & interactive questions on granular data BROAD Big data, many data types HIGH SPEED Fast response-time, interactivity SIMPLE No data preparation, no pre-aggregates, no tuning DEEP Complex & interactive questions on granular data SIMPLE No data preparation, no pre-aggregates, no tuning REAL -TIME Recent data, preferably real- time HIGH SPEED Fast response-time, interactivity OR Technology today requires tradeoff A breakthrough in today’s information processing architecture is needed
  • 18. CPU STORAGE MEMORY Compression PartitioningOLTP+OLAP in column Store Insert Only on Delta No Aggregate tables (Dynamic Aggregation) Solid State Flash HDD 64bit address space 1 TB in current servers Dramatic decline in price/performance L3 Cache L3 Cache L3 Cache L3 Cache L3 Cache L3 Cache L3 Cache L3 Cache Multi-Core Architecture 8 CPU x 10 Cores per blade Massive parallel scaling with many blades Logging and Backup Next-generation Software & Hardware Architecture Removing data processing bottlenecks using latest innovations in computing
  • 19. ACID Compliant Database In-Memory Column Store Out In SQL BICS MDX OData HANA Studio Data Services HS Bulk Loader SLT DCX (SAP Data) Parallel Calculations Scripting Engine Business Function Library Unstructured (Text) Predictive Analysis Library OLAP XS App Server “R” HS Integration Batch Transfer SAP & Non-SAP Extensive Transformations Structured & Unstructured Hadoop Integration Near Real Time SAP & Non-SAP ODBC / JDBC 3rd Party Apps 3rd Party Tools BICS NetWeaver BW SAP BOBJ ODBO MS Excel 3rd Party OLAP Tools HTTP RESTful services JSON / XML “R” ESP What Makes HANA the Platform of Choice?
  • 20. What’s the Difference? Column Store vs. Row Store? Data - 8 billion humans Attributes:  first name  last name  gender  country  city  birthday  ~ 200 bytes Query:  How many women?  How many men?
  • 21. Data - 8 billion humans  Query: How many women, how many men?  Row Store – Stride Access “Gender”  8B tuples x 64 byte ≈ 512 GB  Assuming a scan rate of 2MB/Sec/Core scan with 1 core will take 256 Seconds Table: World Population FirstName LastName Gender Country City Birth Data - 8 billion humans  Query: How many women, how many men?  Row Store – Complete Scan  8B tuples × 200 bytes per tuple ≈ 1.6 TB  Assuming a scan rate of 2MB/Sec/Core A complete scan with 1 core will take 800 Seconds Table: World Population FirstName LastName Gender Country City Birth What’s the Difference? Data representation in a row store 1 2 3 8 x 109 rows 1 2 3 8 x 109 rows
  • 22. What’s the Difference? Data representation in a column store Data - 8 billion humans  Column Store  Dictionary of Names, Countries, Cities…  ≈ 700 MB  8 B Records × 91 bytes per tuple  ≈ 91 GB  Table Size: 91GB + 700MB ≈ 92 GB  Column Store Compression 17:1 Column Table: World Population FirstName LastName Gender Country City Birth 1 2 .. 200 .. 40000 .. 1x106 .. 5x106 .. 8x106
  • 23. What’s the Difference? Data representation in a column store Data - 8 billion humans  Column Store  Dictionary of Names, Countries, Cities…  ≈ 700 MB  8 B Records × 91 bytes per tuple  ≈ 91 GB  Table Size: 91GB + 700MB ≈ 92 GB  Column Store Compression 17:1 Query:  How many women, how many men?  8B x 2 bytes for “Gender” ≈ 1 GB  Assuming a scan rate of 2MB/Sec/Core A complete scan with 1 core will take 0.5 Seconds 1600:1 or “stride” 512:1 Column Table: World Population FirstName LastName Gender Country City Birth 1 2 .. 200 .. 40000 .. 1x106 .. 5x106 .. 8x106  Full Column Scan on “Birthday”?  8B x for “Birthday” ≈ 16 GB  Assuming a scan rate of 2MB/Sec/Core A complete scan with 1 core will take 8 Seconds
  • 24. Order Country Produc t Sales 456 France corn 1000 457 Italy wheat 900 458 Spain rice 600 459 Italy rice 800 460 Denmark corn 500 461 Denmark rice 600 462 Belgium rice 600 463 Italy rice 1100 … … … … Columnar Dictionary Compression • Dictionary per column • Uses data-driven fixed-length bit encodings • Operations directly on compressed data, using integers • More in cache, less main memory access 1 Belgium 2 Denmark 3 France 4 Italy 5 Spain 1 3 2 4 3 5 4 4 5 2 6 2 7 1 8 4 … … 1 7 2 5,6 3 1 4 2,4,8 5 3 Logical Table Dictionary 5 entries, so need 3 bits to encode! Compressed column (bit fields) Inverted index Dictionary Where was order 460? Which orders in Italy?
  • 25. Elimination of Aggregates • Traditional applications use “materialized aggregates” (tables with min/max/sum/avg…) to increase analytic performance • These aggregates must be recomputed after data changes, or at scheduled times • HANA aggregates massive data-sets on-the-fly with high performance => no need to save aggregates • Means: – Simpler data models and application logic, – More up-to-date – Less log activity
  • 26. Other Advantages of Columnar Tables • Scanning column data is so fast that indexes are usually not required – Saves memory as well as index update time • Dynamic views computed on the fly • Very fast full column aggregations, due to encoding and partitioning (>1 B records per second) • Add a new column to a table without a complete table re-organization • Very efficient projections (bit-vector operations) • Compression reduces main-memory access – Performance bonus due to improved cache behavior Using SAP HANA, table data may be compressed up to 5x!* * Data dependent, please refer to the HANA sizing guide; YMMV
  • 27. One in-memory atomic copy of data for Transactions + Analysis  Eliminate unnecessary complexity and latency  Less hardware to manage  Accelerate through innovation and simplification  3 copies of data in different data models  Inherent data latency  Poor innovation leading to wastage Separated Transactions + Analysis + Acceleration processes SAP HANA (DRAM) Transact ET L Analyze ET L Re-think Data Management with in-memory computing Need to eliminate redundant data copies, materialization and models A Common Database Approach for OLTP and OLAP Using an In-Memory Columnar Database Hasso Plattner VS Accelerate Cache
  • 28. Any Apps Any App Server SAP Business Suite and BW ABAP App Server JSONR Open ConnectivityMDXSQL SAP HANA Platform – More than just a database SAP HANA platform converges Database, Data Processing and Application Platform capabilities & provides Libraries for predictive, planning, text, spatial, and business analytics so businesses can operate in real-time. SAP HANA Platform UnifiedAdministration Life-cycleManagement Security Extended Application Services Integration Services Deployment: Database Services ApplicationDevelopment ProcessOrchestration OLTP | OLAP | Search | Text Analysis |Predictive | Events | Spatial | Rules | Planning | Calculators Processing Engine Application Function Libraries & Data Models Predictive Analysis Libraries | Business Function Libraries | Data Models & Stored Procedures Data Virtualization | Replication | ETL/ELT | Mobile Synch | Streaming App Server| UI Integration Services | Web Server On-Premise | Hybrid | On-Demand Supports any Device
  • 29. Renovate existing systems while enabling future breakthroughs Operational Analytics Big Data Warehousing Predictive, Spatial & Text Analytics REAL-TIME ANALYTICS SAP HANA PLATFORM Sense & Respond Planning & Optimization Consumer Engagement REAL-TIME APPLICATIONS SAP BusinessSuite SAP BusinessOne 40+ HANA Apps, Accelerators & RDS StartUps & ISV Apps Operational Datamarts Enterprise Data Warehouse & BW on HANA SAP HANA Platform Administration Extended Application Services Integration Services Deployment: Database Services Development Processing Engine Application Function Libraries & Data Models On-Premise | Hybrid | On-Demand
  • 30. Consumer Engagement Applications Game-changing innovation with new applications and business models Real-time Engagement for consumers Real-time insights for enterprise  Generate real-time consumer insights  Deliver personalized, engaging experiences  Create more responsive business with precision targeting • HTML-5 support • Mobile integration • Consumer-grade usability • OLTP + OLAP real-time Processing • Sentiment Intelligence • Predictive analytics SAP HANA PLATFORM
  • 31. Sense & Respond Applications for Internet of Things Faster execution by adjusting to signals in the business environment  Detect and analyze data trends by aggregating sensor data  Benefit from more energy efficient logistics, transforming retail distribution  Increase quality of life through intelligent buildings, robots, cars and cities • Event stream processing (ESP) • No data preparation • RFID Integration • Embedded data processing • Machine Learning • Spatial Processing Smart Cities Smart Automobile Smart Equipment Smart Logistics Smart House Smart Vending Connected Cars
  • 32. Planning and Optimization Applications Faster execution to adjust to changes in the business Sales and Operations Planning Business Planning and Consolidation  Enable iterative period end closing with continuous posting into accounts  Cash forecasting management  Optimize procurement, manufacturing, transportation without limits • In-memory stored procedures • Integrated Planning and Calculation engines • Predictive Analytics and Business Functions • Recent data, preferably real-time • Supporting complex questions on interactive data • Built-in Spatial Processing
  • 33. SAP Business Suite powered by SAP HANA SAP HANA PLATFORM SAP ERP SAP CRM SAP SCM SAP SRM Smarter business innovations Unlock new growth opportunities before your competitors do Faster Business Processes Drive your business at the speed of the market Simpler Business Interactions Empower people to decide and act in the business moment
  • 34. SAP HANA (DRAM) Operational ad-hoc analytics and monitoring Real-time insight into the in-the-moment business situations  Accelerate business decisions Provides vision across entire business process  Empower front-line employees Provide POS data analysis as interactive session with drill-down information  Implement real-time fraud detection, risk management and monitoring Pricing Accounting Customers Forecasting Planning Channel Inventory Products Suppliers Customer Service Finance and Operations Account Administration • OLTP + OLAP Processing • SAP HANA Live • SAP smart data access – data virtualization • Real-time data integration (Replication, Streaming) • Unified data modeling • Single-query access to data
  • 35. SAP BusinessWarehouse Powered by SAP HANA SAP HANA PLATFORM Data Manageme nt Data Storage Analytical / Planning Engine DATA MODELING SAP NetWeaver BW QUERY REPORTING ANALYTICS SAP BOBJ Busines Intelligence Dramatically Improved Performance Improved decision making, faster reporting, and the most up-to-date information Simplified Administration and Streamlined Landscape Reduced administration and lower TCO Unlock The Power of Your Data Across The Enterprise Self-service access to all information at the most granular level
  • 36. Predictive Analytics & Machine Learning Transforming the Future with Insight Today  Provide Business Analysts with sophisticated algorithms to take the next step in understanding their business and modeling outcomes.  Perform statistical analysis on your data to understand trends and detect outliers in your business.  Build models and apply to scenarios to forecast potential future outcomes  Combine, manipulate and enrich data to apply it to your business scenarios. Self-service visualizations and analytics to tell your story • OLTP + OLAP Processing • SAP HANA Live • SAP smart data access – data virtualization • Real-time data integration (Replication, Streaming) • Unified data modeling • Single-query access to data
  • 37. SAP HANA Spatial Processing Develop and deploy spatially-enabled analytics and applications Transaction Data Unstructured Data Location Data Machine Data SAP HANA Analytics Applications Visualization GIS SAP Info Access (HTML 5) Mobility REAL-TIME DATA SPATIAL DATA BUSINESS DATA OLTP Analytics Planning Predictive Text Spatial Geo- Services Geo- Content Columnar Spatial Processin g Calc Model / Views Spatial Functions Spatial Data Types Real-time high-performance spatial processing Store, process, manipulate, retrieve and share spatial data Unified modeling platform Combine spatial with business data Geo-content and services
  • 38.  File Filtering  Unlock text from binary documents  Ability to extract and process unstructured text data from various file formats (txt, html, xml, pdf, doc, ppt, xls, rtf, msg)  Load binary, flat, and other documents directly into HANA for native text search and analysis  Native Text Analysis  Give structure to unstructured textual content  Expose linguistic markup for text mining uses  Classify entities (people, companies, things, etc.)  Identify domain facts (sentiments, topics, requests, etc.)  Supports up to 31 languages for linguistic mark-up and extraction dictionary and 11 languages for predefined core extractions SAP HANA Text Analysis Extract information from documents. Perform text analysis on unstructured data SAP HANA Text Analysis
  • 39. Renovate existing systems while enabling future breakthroughs Operational Analytics Big Data Warehousing Predictive, Spatial & Text Analytics REAL-TIME ANALYTICS SAP HANA PLATFORM Sense & Respond Planning & Optimization Consumer Engagement REAL-TIME APPLICATIONS SAP BusinessSuite & SAP BusinessOne 30+ HANA Apps, Accelerators & RDS StartUp & ISV Apps Operational Datamarts EDW on HANA (BWonH) SAP HANA Platform Administration Extended Application Services Integration Services Deployment: Database Services Development Processing Engine Application Function Libraries & Data Models On-Premise | Hybrid | On-Demand
  • 40. Uncover value Create breakthroughs Experience simplicity INNOVATIONS PREVIOUSLY UNFEASIBLE • Real-time genome analysis • Instantaneous fraud detection • Predictive maintenance • Optimize procurement, manufacturing, transportation • Real-time MRP with instant re-planning SIMPLICITY PREVIOUSLY UNACHIEVABLE • Transactions and analysis in one system • Efficiently analyze structured and unstructured data • Fewer systems needed • Hardware cost savings • Less DBA involvement needed SAP HANA In-Memory Transaction & Analysis directly In-Memory VALUES PREVIOUSLY UNATTAINABLE • Iterative period end closing • Cash forecasts/management • Real-time offer calculation • In-moment sales forecast • Self-service apps with instantaneous response • Interactive POS data analysis
  • 41. Steven Jones Solution Architecture, Amazon Web Services
  • 42. Over 18 Joint SAP & AWS Solutions • SAP Cloud Appliance Library: http://www.sap.com/pc/tech/cloud/software/appliance-library/index.html • SAP HANA One on the AWS Marketplace https://aws.amazon.com/marketplace/ • SAP HANA AWS Infrastructure as a Service Offering to 1.22TB http://marketplace.saphana.com/ • SAP BW Powered by SAP HANA Trial Offer - Link • SAP on AWS information on the SAP Home Page on AWS.com: http://aws.amazon.com/sap/
  • 43. HANA on AWS - Start Small and Scale As Needed Try Develop Run • Start with SAP BW on HANA Trial for 30 days • Get set up in less than 30 minutes • Pre-built content and sample data • Use the system as-is or load your own data and objects • Built-in tutorials and community support • Choose SAP HANA developer edition or SAP HANA One • Develop, test, and demo applications on top of the SAP HANA platform • Easily accessible and rapidly deployable • Pay for only what you use • Community Support • Two options for production workloads: • SAP HANA One to instantly deploy a single instance of SAP HANA • SAP HANA (BYOL) for real-time provisioning on AWS using existing SAP HANA licenses • Various support options available
  • 44. Use Cases / Architecture Patterns
  • 45. Customer Data Centers VPN or Direct Connect Virtual Private Cloud SAP HANA Disaster Recovery (DR) on AWS DR ECC BWBW ECC PRD SAP production (PRD) landscape runs in customer’s own datacentre SAP development & quality assurance landscape runs on AWS SAP HANA Appliance(s) HANA DB SAP HANA System Replication (Async)
  • 46. Customer Data Centers VPN or Direct Connect Secure connectivity between datacentre & AWS Virtual Private Cloud Hybrid HANA Deployment – Customer Data Centre & AWS DEV QAS ECC BW ECC BW BW ECC SRM PRD SAP production landscape runs in customer’s own datacentre SAP development & quality assurance landscape runs on AWS SAP HANA Appliance(s) HANA DB HANA DB
  • 47. Virtual Private Cloud Full SAP HANA Deployment on AWS DEV QAS Customer runs DEV, QAS, & PRD on AWS PRD VPN or Direct Connect Secure connectivity between LAN & AWS network Customer LAN ECC BW ECC BW HANA DB HANA DB ECC BW HANA DB
  • 48. Virtual Private Cloud SAP HANA for Big Data Analytics VPN or Direct Connect Secure connectivity between LAN & AWS network Customer LAN ECC BW BW HANA DB SAP BI Amazon EMR +
  • 49. SAP HANA Scalability Test for SAP BW Using In-Memory Data Fabric  111 SAP HANA Instances (1,776 CPU Cores)  8M Rows loaded per second (60 Billion Total)  220ms single node query (600 Million Rows)  330ms for federated query (60 Billion rows)  Throughput of 3 million queries per hour Additional Details: http://bit.ly/scale-hana-aws
  • 50. Deployment of SAP HANA on AWS
  • 51. 10 Regions* 26 Availability Zones* 51 Edge Locations * China (Beijing) Region- EC2 Availability Zones: 1 Coming Soon Global Infrastructure
  • 52. Amazon EC2 Cluster Compute Instances for SAP HANA 2 x Intel Xeon E5-2680 v2 processors (Ivy Bridge) 32 vCPUs with hyperthreading 64-bit 60 GB RAM 10 Gigabit Network Enhanced Networking 2 x Intel Xeon E5-2670 processors (Sandy Bridge) 32 vCPUs with hyperthreading 64-bit 244 GB RAM 10 Gigabit Network NUMA and Turbo Support c3.8xlarge cr1.8xlarge 2 x Intel Xeon E5-2670 v2 processors (Ivy Bridge) 32 vCPUs with hyperthreading 64-bit 244 GB RAM 10 Gigabit Network NUMA and Turbo Support Enhanced Networking r3.8xlarge HANA One SAP HANA Infrastructure Subscription
  • 53. SAP HANA Deployment Methods AWS Global Infrastructure AWS QuickstartAWS Marketplace SAP Cloud Appliance Library AWS API’s AWS CloudFormation Developer Edition / Trials BYOL (Multi-Node)HANA One SAP HANA Marketplace SAP HANA
  • 54. Wrap Up
  • 55. SAP and Women’s Tennis Association (WTA) Solution Overview Court Cameras Umpires Player Data Journalists Players & Coaches Fans SAP WTA Player Analytics Powered by SAP HANA Data Sources Mobile Apps SAP HANA One SAP Data Services SAP BusinessObjects BI
  • 56. Kellogg Uses AWS to Save $900,000 over 5 Years Over Using On- premises Infrastructure Kellogg produces breakfast foods for more than 180 companies worldwide, with annual revenue of almost $15 B. Using AWS saves us $900,000 in infrastructure costs alone, and lets us run dozens of simulations a day so we can reduce trade spend. It’s a win-win. • Needed a better way to track and model promotional costs (“trade spend”) to improve the bottom line—and needed to be able to run more than 1 trade-spend simulation/day • Running SAP Accelerated Trade Promotion Planning (TPM) – Powered by SAP HANA • By using SAP HANA on AWS, Kellogg estimates it will save $900,000 over 5 years versus traditional on- premises infrastructure alternatives • Increased business agility: Company can run dozens of trade spend simulations each day, and decreases deployment time by 30x • Leveraged existing SAP HANA software license investment on AWS • Familiarity and Accessibility of the AWS platform enabled engineers to easily apply their existing knowledge and infrastructure skills Stover McIlwain Senior Director of IT Infrastructure Engineering ” “
  • 57. “ ” Mantis Technology Group – Internet Software solution provider specializing in enterprise custom services for online retailers & high transaction volume provision systems Product: Pulse Analytics – Social Media Analytics By SAP HANA One (Cloud) Business Challenges/ Objectives  Offer rapid analysis of social media channels to track consumers and influencers and measure brand against industry metrics  Scale its social media analytics service offering to handle ever increasing volumes of data cost-effectively Technical Challenges  Reduce cost of managing cluster of 18 Text Analysis XI and 3 MySQL servers  Analyze large volumes of social media data – more than 1M documents daily up to 4M  Reduce the ETL load times to deliver real-time analysis Benefits  Faster SAP HANA’s native Text Analysis and sentiment analysis with topic identification  New real-time analytical capabilities allow for visual presentation of data that is free from previous performance-based constraints  Data Architecture simplification by replacing 20+ separate servers with 1 instance of SAP HANA One Significant Simplification of Data Architecture Moved from 23 servers to 1 Hana One server 99% faster Significantly reduced ETL Load time 6x faster Text analysis processing “We can get close to an order of magnitude improvement in performance, additional headroom, access to new practical capabilities (as a result of the performance improvements) AND… still save money!” Doug Turner, CEO of Mantis Technology Group
  • 58. Technical Implementation • 1. Key SAP HANA features • SAP HANA One: In-memory processing in the cloud • Native text analysis functionality in SAP HANA for full-text indexing, fuzzy search and sentiment analysis • Automatic Data Indexing Capabilities • Join Data on all dimensions as it is created • Fuzzy Search for advanced clustering of similar mentions • On-premise capabilities • 2. Technical KPIs • Significantly reduced ETL data load • 6x increase in query speed • Simplification of data architecture • 3. Implemented by Mantis Technology Group 4. Partners • Data Center provided by Amazon SAP HANA Platform • Architecture Diagram 5. Next Steps  Go-live on SAP HANA One by SAPPHIRE Text Analysis SocialSentimentAnalysisSocialSentimentAnalysis Social Media Channels ETL Process Data Mart Collection DB Text Analysis Previous Architecture Diagram HANA Architecture Diagram Social Media Channels
  • 59. “We gather huge amounts of data from the field every second. For us, Business Intelligence is not about yesterdays or last week report, it's about NOW… In our industry' it's hard to attract and retain highly qualified dedicated employees. Our highly advanced mobile applications grant the truck driver sense of pride. They feel they contribute to our service mantra in a visible way. They do not perceive themselves as "blue-collar workers" anymore.“ Dror Katz, Katz Logistics CEO “ ” Mobideo – Professional Service First startup to bring productive customer to SAP HANA One Product: Provides real time analysis using Joint Solution by Mobideo and SAP HANA ONE Business Challenges/ Objectives  Deploy easy access to information in real-time  Ensure the compliance with protocols  Deploy the monitoring and alerts for effective management Technical Challenges  The current systems have limited ability to provide granular visibility  Provides solution that capture and available analysis in real time. Benefits  Main cases: Katz Group (logistic Industry) and Radwin (Telecommunications)  Improve providing real time visualization and dashboards for yours customer´s managers.  Significant Improves on the operation management through real time monitoring and smart alerts possible by integration with SAP HANA and local devices.  Provides the most granular level of the visibility, compliance and adaptability across the lifecycle of the operation. Real-Time Monitoring and Smart Alerts Significant Improvement In the Visibility and Performance Analysis Scalability Radwin has an extensive network (~100 countries)
  • 60. SAP HANA • 4. Architecture Diagram Technical Implementation 1. Key HANA features  Data Extracting/ Loading  Integrate HANA with Business Objects, Visual Intelligence, Visual Enterprise 2. Technical KPIs  Significantly improved data Processing  Highly improved report performance 3. Implemented by Mobideo  Estimated Project Services – Project Duration – Months 4. Partners  SAP HANA ONE  Data Center provided by Amazon Solution Provide by Mobideo SAP Business Objects Dashboards, What-if Analysis, Analytics Reports, ad-hoc Analysis Mobideo Studio Mobideo Engine Mobideo Web Portal ERP Legacy System s Others Process forms &Support documents• Iphone Windows Mobile Android Windows 7/8
  • 61. SAP HANA on AWS “Pilot” Program Offer • Customers may receive up to US$1,000 in AWS Promotional Credits to evaluate SAP HANA on a much larger instance (Amazon EC2 cr1 or r3.8xlarge Instance type) • The credit will fund the AWS infrastructure costs for customers to trial SAP HANA through a choice of deployment methods: – The SAP Business Warehouse (BW) Trial powered by SAP HANA on AWS or the SAP HANA Infrastructure subscription offering-both offered and available through SAP – Or if the customer has their own license of SAP HANA, they may leverage it in a “BYOL” model and use the SAP HANA on AWS Quick Start Reference Deployment Guide as a tool to setup and run it themselves on the AWS Cloud • Learn more about the Pilot offer, including terms and how to apply for up to US$1,000 in AWS Promotional Credits at http://aws.amazon.com/sap/saphana/pilot/
  • 62. Where to Find SAP HANA on AWS Resources  Latest updates  How to Get Started  Deployment Information  Support Information  SAP HANA on AWS Implementation and Operations Guide Contact us: saphana@amazon.com http://aws.amazon.com/sap/saphana/ SAP HANA in the AWS Cloud Quick Start Deployment Guide http://aws.amazon.com/quickstart/
  • 63.  What is your cloud strategy?  How do you get there?  What are the risks and rewards?  What is the business case? Discussion and Next Steps