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Optimizing Your Big Data Environment to Maximize Your SAP Investment

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In this age of big data, new technologies and methods have evolved and matured to the point where organizations are able to store and exploit the increasing volume, variety, and velocity of data and …

In this age of big data, new technologies and methods have evolved and matured to the point where organizations are able to store and exploit the increasing volume, variety, and velocity of data and achieve true actionable intelligence to increase profits, enhance operational efficiency, and gain a competitive edge in the marketplace. Today’s business leaders are increasingly demanding integration with external sources such as social media, the Internet of Things, and data provided by third parties, in order to derive these meaningful and actionable insights.

Capgemini has a proven track record of assisting our customers exploit emerging technologies (such as Hadoop) together with their existing investments in advanced, in memory data platforms (such as SAP HANA) to create an optimized Big Data Environment that helps the organization achieve significant additional value from their data in return for relatively modest additional capital investment. By optimizing the environment and leveraging new technologies to compliment and extend the reach and capability of existing solutions, we help extend the value, reach, and capability of these existing investments and provide our customers with a richer analytical experience.

Join Capgemini to learn how we can assist SAP customers design and implement a robust reporting and analytics infrastructure that will transform big data into intelligence and intelligence into action.

Presented at SAPPHIRE NOW 2014.

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  • 1. Proprietary & Confidential Optimizing your Big Data environment to maximize your SAP investment The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved. Steve Stone – Capgemini Advanced Solutions Leader (NA Business Information Management) Scott Schlesinger – Senior Vice President; NA Business Information Management Leader
  • 2. 2The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved. What is transpiring in the market? Exclusive Research from CIO magazine JANUARY 2014 2014 State of the CIO SURVEY 1
  • 3. 3The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved. Customer  Value   Information DeliveryInformation Supply & Integration Project-­‐Marts   Project   Data   Project   Data   Project   Data   EDW   Supplier   Product   Customer   Finance   Subject  Area  Data   Other   Other   Sandbox   TransAct  Data   Staging  &  PSA   ODS   Information Management   Program & Data Governance Master Data Management Data Quality Framework CRMERPHROther Mobile   Self-­‐Service   Social  Media   Volume   Variety   Velocity  Sources   Internet Cloud Identify Organize ActAcquire Use Case Analyze Information Landscape Transformation The “New Normal” facing today’s data driven Organizations
  • 4. 4The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved. What is the driving force for this New Normal? Data explosion - creating opportunities to leverage Hadoop to offload data: Increased costs to store and use large volumes of data (structured, semi-structured, and unstructured) •  Wal-Mart handles more than 1 million customer transactions every hour, which is imported into databases estimated to contain more than 2.5 Petabytes of data. •  More than 5 billion people are calling, texting, tweeting and browsing on mobile phones worldwide •  100 terabytes of data uploaded daily to Facebook •  According to Twitter's own research in early 2012, it sees roughly 175 million tweets every day, and has more than 465 million accounts. Desire (inability) to look forward - creating opportunities to use new data leveraging Advanced Analytics •  Life Sciences organizations want to reduce the time to market of new, effective, safe drugs. However, clinical trial data, drug efficacy data, and market data is generally stored in various formats in various systems challenging their ability to make valid data correlation and effective, predictive results •  Retailers want to understand and predict how a new product will sell in a new market. However, all too often there is no efficient means to organize distributed social media data and couple with sales and demographic data to predict product performance
  • 5. 5The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved. What does a truly Optimized Environment offer? Efficiency of data storage Reduced investment in simply storing data Increased Analytics and insights Moving data to online storage where it is accessible in its various forms Offloading select data from legacy storage mediums and platforms to low-cost, commodity hardware Combining structured and unstructured data to drive innovation thru analytics Benefits ! Substantial Data Storage Cost Reduction freeing up funds to use for high value Analytics (self funding projects) ! Remove data from cold storage (tape) and make available for analysis ! Significant performance gains to your legacy environment ! Ability to perform analytical functions that were previously impossible leveraging existing and newly captured data ! Unlock significant untapped Business Value Data Optimization
  • 6. 6The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved. HANA is a key Component of an Optimized Data Strategy HOT •  Data is read and/or written frequently •  In-Memory •  All HANA features can be leveraged •  Recent Postings, Real Time Analytics, Management Reports, etc WARM •  In-frequent access •  No need to keep in memory all the time •  All HANA features can be leveraged •  Older content - prior year Management Reports, yearly or quarterly data COLD •  Sporadic access •  Data stored outside HANA – NLS storage •  Features limited by NLS capabilities •  Sporadically accessed video content, data archived for older years etc DATAVOLUME PERFORMANCE As  an  extension  of  a  BI  Strategy,  this  approach  allows  for  the  inclusion  of  unstructured  data,  leveraging   technologies  such  as  Hadoop  and  HANA  as  the  In-­‐Memory  platform  for  most  of  the  critical  analytics,  while  less   expensive  platforms  could  be  leveraged  for  “colder”  data  and  analytics.     Examples  
  • 7. 7The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved. Utilities/Energy Companies: "  Looking to move from Smart Meter to Smart Charging for load balancing. Time & Load based charging & notification "  Proactive Customer Intervention based on load prediction to reduce need to turn on “peakers “ "  Predictive Asset tracking and management Business Use Cases Across Various Sectors Organizations of all types and of all sizes are thirsting for knowledge and need new means to acquire, store, organize, optimize data Telecommunication Companies: "  Analyzing call data records in real time to identify fraudulent behavior as well as Churn triggers immediately "  Tailoring marketing campaigns to individual customers using location- based and social networking technologies "  Using insights into customer behavior and usage to develop new products and services Life Sciences Organizations: "  Desire to reduce the time to market of new, effective, safe drugs. However, clinical trial data, drug efficacy data, and market data is generally stored in various formats in various systems challenging their ability to make valid data correlation and effective, predictive results Retailers: "  Desire to understand and predict how a new product will sell in a new market. However, all too often there is no efficient means to organize distributed social media data and couple with sales and demographic data to predict product performance SAP HANA 0.0 sec Instant Results + = HADOOP Infinite Storage Real Time Business Results from Big Data
  • 8. 8The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved. HANA Use Cases – Ask yourself: What could make a difference? SAP  HANA   •  Sales Analysis •  Channel Performance •  Segmentation •  Product Launch •  Market Intelligence •  Contract & Revenue Mgmt. Commercial  Analytics   Big  Data  and  Analytics   •  Predictive Asset Maintenance •  Trade Analytics •  Sentiment Analysis •  Products Online •  Personalization Supply  Chain   •  Collaborative demand reconciliation •  Multi-level inventory optimization (SmartOps) •  Increased forecast/planning frequency •  Scheduling simulations/modeling •  Sales & Operations Planning Finance   •  Order to cash •  Minimum margin notifications •  DSO by product or service •  Profitability/margin (COPA) •  Financial close •  Management Reporting •  Forecasting / Planning Quality   •  Complaint tracking •  Product/material analysis •  Supplier performance •  Scrap Cost Management •  Yield Analytics HANA  can  provide  the  central  platform  capability  to  support  new  as  well  as  complex  analytics  .  
  • 9. 9The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved. Amazon Cloud Dashboard & Analytics tools Source ERP/ Datawarehouse Solution Mobile Apps & Enablement In-memory Analytics Accelerator (HANA) Data Loading & Integration AWS S3 File System Datamart Capgemini’s Elastic Analytics is an end-to-end cloud solution that enables you to benefit from advanced analytics via Amazon Web Services (AWS). Get Immediate Business Insights – from Strategy to Execution in minutes using a Cloud based solution to quickly see “the art of the possible” Benefits: "  Can be made available within minutes "  Robust enterprise-ready platform "  Pay only for time used, no infrastructure costs, and no lead- times "  Supports many leading BI software solutions and so can have same look and feel as your own data center "  Completely scalable to meet the demands of the business