Top Analytic Trends


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Presentation given at the SAP Innovation Forum Big Data Track in Stockholm, Sweden, March 2014

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  • More data – unstructured, sentiment, internet of things, sensors…More features – mobile, cloud, advanced analytics…More vendors – hot topic, wide market, market share for allMore maturityMore awareness – from geek to chic
  • In their October 2012 Harvard Business Review article Thomas H. Davenport and D.J. Patil referred to data scientist as the hottest new job of the century.Data you don’t own (twitter in your data warehouse?!)
  • Exposing what was previously invisibleInternet of Things
  • Connected tennis raquet. Babolat unveils yet another breakthrough innovation to the game of tennis: the new Babolat Play Pure Drive. Babolat Play, the world’s first connected tennis racquet, allows every player to live a unique experience based on progression, fun and sharing. Sensors integrated into the handle of the Babolat Play racquet allow players to have access to exciting data about their game including shot power and ball impact location, adding concrete information to the sensations they already receive. 
  • Under Armour
  • >1m data points per day and growing (~10% customers with smartphones)
  •> 40 billionevents per year analyzedUp to 20 % extended tire lifespanUp to 3% reduction fuel& tire costsScenario: Record, transmit and analyze tire information in real time using SAP HANA predictive analytics and geospatial functions Business Challenges/ ObjectivesEnable fleet manager to deliver new services that monitor tire usage and predict maintenance Deliver timely insight each month on cost / profitability analysis, sales & distribution, and supply chain managementTechnical ChallengesProcess and analyze large volume of data real time: 40 billion events per year (600 fleets per system,1.000 assets (trucks etc.) per fleet,6 active tires / asset,1 message / tire / every 2min, 16 h a day,6 days a week)Analyze tire data (pressure, temperature) from sensors, GPS data, and customer records in real-time to predict diagnostic / maintenance workBenefitsIncreased competitiveness and innovation with new technology Increased customer satisfaction with proactive maintenance of tiresLower running costs by cutting fuel consumption Extended the tire lifespan Improved safetyCompany ProfileFounded in 1872, Pirelli is the fifth biggest tire maker in the world in terms of sales. Present in over 160 countries, today it has 22 tire production facilities located on four continents and counts about 37,000 employees. Pirelli estimates its value at €2.27 billion.Pirelli has been an SAP customer for a long time, running several solutions in the SAP Business Suite, including ERP, CRM and SRM to name a few. With SAP HANA, Pirelli is looking to deliver real-time analytics to provide insight on cost/profitability analysis, sales & distribution, and supply chain management.In addition, Pirelli is interested in working with SAP as a valued partner to develop innovative solutions. In particular, Pirelli is developing a new services, Web-based application that runs on SAP HANA to provide fleet managers of vehicles the ability to gain new insight on the use of tires, predict maintenance, and increase customer satisfaction.Inside of each tire is a sensor that collects data relating to pressure, temperature and identification which is can be transmitted to the driver, fleet manager or dealer, allowing them to plan diagnostic and maintenance work, which guarantees the best possible safety standards for every vehicle in the fleet”With SAP HANA, Pirelli can capture and store and analyze data from multiple fleets to discover new insights, such as correlating street conditions, climate and local practices, and using that insight to improve product quality and performance”1. Key SAP HANA featuresPredictive AnalyticsGeospatial SupportIntegrated Application Services (XS) / Mobile ApplicationsReal-Time Analytics for SAP Business Suite reporting (cost/profitability analysis, sales & distribution, supply chain)2. Technical KPI’sFuel consumption, tire lifespan, early warnings:Fast DeflationLow PressureService IntervalTemperature MonitoringEfficiency Level 3. Co-Innovation with SAP 3 month of development4. PartnersSpecTec (
  • Mantis Pulse – SAP data services to SAP HANA in the cloud, leverages Text Analysis.
  • One reason chose – ease and agility… Understand and connect with votors and donors at a more granular and personal levelImprove on previous analytic agility and speedIntegrated data from digital and other channelsContinual voter modeling using KXEN to predict voter segment receptiveness and behavior66,000 election simulations per night….Raised $1bn in campaign funds, with fewer resources, by communicating with the right individuals at the right time on the right medium Grew digital fundraising by 20%, added 500,000 donors, increased ad buying efficiency by 15% and improved volunteer and per-donor rates over 2008“,” by Michael Scherer, Time, November 7, 2012.“We analyzed very early that the problem in Democratic politics was you had databases all over the place,” said one of the officials. “None of them talked to each other.” So over the first 18 months, the campaign started over, creating a single massive system that could merge the information collected from pollsters, fundraisers, field workers and consumer databases as well as social-media and mobile contacts with the main Democratic voter files in the swing states.The new megafile also allowed the campaign to raise more money than it once thought possible. Until August, everyone in the Obama orbit had protested loudly that the campaign would not be able to reach the mythical $1 billion fundraising goal.“We ran the election 66,000 times every night,” said a senior official, describing the computer simulations the campaign ran to figure out Obama’s odds of winning each swing state. “And every morning we got the spit-out — here are your chances of winning these states. And that is how we allocated resources.”In late spring, the backroom number crunchers who powered Barack Obama’s campaign to victory noticed that George Clooney had an almost gravitational tug on West Coast females ages 40 to 49. The women were far and away the single demographic group most likely to hand over cash, for a chance to dine in Hollywood with Clooney — and Obama.So as they did with all the other data collected, stored and analyzed in the two-year drive for re-election, Obama’s top campaign aides decided to put this insight to use. They sought out an East Coast celebrity who had similar appeal among the same demographic, aiming to replicate the millions of dollars produced by the Clooney contest. “We were blessed with an overflowing menu of options, but we chose Sarah Jessica Parker,” explains a senior campaign adviser. And so the next Dinner with Barack contest was born: a chance to eat at Parker’s West Village brownstone.Read more:
  • Analytics is no longer something you do “on” the business – it’s part of what you sell
  • …rather than a byproduct
  • minding your digital business
  • Immersive, personalized, customized, simple and seamless, real-timeA major component of MyMagic+ is the new My Disney Experience website and mobile app, which gives guests planning their trip the latest information on all Walt Disney World Resort has to offer. We know that some people like to plan every aspect of their Disney vacation in advance while others like to plan very little, letting their day unfold spontaneously. No matter where guests fall in that spectrum, My Disney Experience gives them the flexibility to plan as much or as little as they’d like to create the exact Disney experience they want. They can book dining and other experiences and reserve times for their favorite attractions, shows and more through an enhanced FastPass system, FastPass+. Once they arrive, they can use their smart phones to spontaneously change their plans in the moment, exploring our parks at their own pace and getting the most out of their visit.Linking the entire MyMagic+ experience together is an innovative piece of technology we developed called the MagicBand. Worn on the wrist, it will serve as a guest’s room key, theme park ticket, access to FastPass+ selections, PhotoPass card and optional payment account all rolled into one. We’ve began testing certain aspects of MyMagic+ in Florida last month and the early reactions we’ve gotten have been fantastic
  • Data is now the heart of your business – not ERPEnterprise data hubs / data lakesGartner Hybrid Transactional Analytical Processing (HTAP)The foundation for “innovation apps” that harness the full power of the “Nexus of Forces” (Gartner) or the “Third Platform” (IDC): analytics, collaboration, mobile, and cloud
  • A. Sandford, NASA Ames Research Center, Mountain View, California. Both samples were prepared by gently desiccating them in a convection oven at low temperature over the course of several days. The dried samples were then mixed with potassium bromide and ground in a small ball-bearing mill for two minutes. One hundred milligrams of each of the resulting powders were then pressed into a circular pellet having a diameter of 1 cm and a thickness of approximately 1 mm. Spectra were taken at a resolution of 1 cm-1 using a Nicolet 740 FTIR spectrometer. Figure 2 shows a comparison of the 4000-400 cm-1 (2.5-25 mm) infrared transmission spectra of a Granny Smith apple and a Sunkist Navel orange
  • Globe and Mail[twitter]Augmenting Hadoop with fast #analytics, using #SAPHANA One on AWS: [/twitter]
  • SAP HANA In-Memory Platform : Complete picture
  • Products ”sell themselves”Discovery has to grow up: from Natural to CivilizedGoverned discoveryDecision-making and smoother ad-hoc analytics in processes
  • So what is a “Network of TRUTH” and why do we care. Lets take a closely related analogy. When people tried to write down facts about the world. They started by writing individual books on one topic at a time. We still have these references.But as those references expanded, querying and retrieving information also slowed down.To get a holistic view we create “Encyclopedia” that collected the knowledge into a single place. Amazing.But think about the Encyclopedia you had as a kid. Sure it had a lot of information, but how often did it get updated. What was the process. Revisions took years and were heavily governed. Even updates to dictionaries were slow and governed. The amount of information was still limited by the process.The next evolution took Encyclopedia into digital (Encarta) and even with the internet the governance process and manufactured nature meant the scale was limited and updates were still slow.Today none of us use Encarta or a paper Encyclopedia. We all employ Wikipedia. It is massively bigger than any prior Encyclopedia, it is more up to date, and it changes constantly.This is where we need to evolve Business Intelligence. Not back to individual books, but forward. We need to take the value of an Encyclopedia, a single collection of knowledge and create something much bigger for our organizations.Wikipedia required multiple things to be true, before it became a practical options, two technologies and a cultural change.The internet had to exist and to flourish that could connect everyone to a shared space.Technology had to be able to support the constantly changing documents (with all the wiki stuff like editing and logging)People had to be comfortable employing technology to perform their research and be willing to engage with the site.
  • The “chauffeur effect”Advanced analytics goes through same trend as data discovery
  • Moving from the period of “chauffeurs” to “drive yourself”
  • Belgacom telephone, Internet, and television services, the peopleof Belgium rely on Belgacom. But, in this highly competitiveindustry, the window of opportunity to introduce new productsis narrow. With the SAP® InfiniteInsight® solution, Belgacom hasautomated data mining tools that help it better understandcustomer needs and provide personalized service andcampaigns across all channels. This means more satisfiedcustomers staying connected with Belgacom.Objectives•• Leverage previously unseen customer insights toreduce customer churn and identify newrevenue opportunities••Enhance churn detection, speed up deploymentfor predictive models, and identify revenue potentialacross the customer lifecycleBenefits••Enables next-best-action marketing across allchannels, from call centers to the Web to retailstores••Optimizes interactions throughout the completecustomer relationship, revealing previouslyunseen customer insights•• Identifies market gaps, turning them into revenue•• Increases customer satisfaction and reducescustomer churn••Raises return on marketing investments••Accelerates modeling time from months to daysBelgacom Delivers NextBest Actions Across AllCustomer ChannelsChallenges▪▪In a highly competitive market, the window of opportunity tointroduce new products or promotions can be short.▪▪Had been using traditional modeling tools that lacked flexibility,were hard to use, and left the company at risk of customer churnor missing critical revenue opportunities.▪▪Former data mining solutions did not easily integrate with theirTeradata data warehouse, and translating models into a usableformat was time-consuming and prone to human error.Solutions▪▪Standardized on InfiniteInsight™ to build predictive models tomanage its business and consumer customer relationships.▪▪Every interaction in the customer lifecycle from acquisition tocross promotions and retention is optimized.▪▪Eliminated lengthy error-prone data preparation processesrequired by the previous solution.▪▪In-database analytic capabilities allowed integration to Teradatadata warehouse out of the box.Results▪▪The InfiniteInsight™ automated approach to data mining hasincreased the company’s agility and allowed a handful of analyststo support the entire business.▪▪Achieving a higher return on marketing investments and visibilityto previously unseen customer insights.▪▪Cut modeling time from months to days; all models are refreshedmonthly or weekly, so the business never has to be satisfied withold, out of date ones.Summary Points:For Belgacom, the window of opportunity to introduce new products or marketing promotions can be short.Every customerinteraction– from acquisition to cross promotions and retention – is optimized with predictive models built on InfiniteInsight.In some cases, they’ve been able to realize up to a four-fold increase in campaign response rates.See full customer story at bottom of notes.Script:Transition: First, let’s look at customer acquisition. In a survey by Piper Jaffrey, nearly 50% of today’s CMO’s focus on new customer acquisition. But the costs across both traditional channels and the cloud are expensive. This means we need to focus our marketing efforts to increase uptake and get the most from our marketing dollars.Belgacom, a leading telecom provider in Belgium is a perfect example of using predictive analytics for customer acquisition. Belgacom is in a highly competitive market, where the window of opportunity to introduce new products or marketing promotions can be short. Prior to InfiniteInsight®, the company relied on traditional modeling tools that lacked flexibility and were hard to use. This left Belgacom exposed to the risk of missing critical revenue opportunities or worse yet, customer churn.Belgacom standardized on InfiniteInsight®. Every interaction in the customer lifecycle – from acquisition all the way through cross promotions and retention – is optimized with predictive models built on InfiniteInsight®. Independent of channel, whether it be the call center, a retail store or the company’s website, customer and prospects are presented in real-time with a personalized offer or next best action. In some cases, they’ve been able to realize up to a four-fold increase in campaign response rates.Background Research (on Customer Acquisition): Full Customer Story…Industry: TelecommunicationsCustomers: Over 90% of Belgium marketUse Case: Churn Status: Approved Press ReleaseResource Center: Customer Presentation: S:\Marketing\Events\2009\2009_EUC\2009_11_Belgacom_HowToPresentDMResults_Public.pdf PR: Industry: TelecommunicationsBelgacom is the main telecommunications company in Belgium and market leader in a number of areas, including: retail and wholesale fixed-line telephony services, mobile communications services broadband data and Internet services.Belgacom created in 2007 a new operational structure based on four pillars: Residential customers are taken care of by the Consumer Business Unit (CBU)Professional customers, meanwhile, benefit from the services of the Enterprise Business Unit (EBU)Service Delivery Engine and Wholesale (SDE&W) groups together the network and IT services. Its wholesale activity offers telecommunications services to other operators and suppliers on the Belgian market.Staff and Support (S&S) brings together all the horizontal functions that support the Group's activities. Scenario Enhance current churn detection process, speed up overall model deployment, estimate potential revenue per customer amd call volumes per region.Challenge Highly competitive marketSolution Products: Modeler, K2S, KEL, Explorer, Scorer for TeradataInfiniteInsight® connects directly to Teradata Models “in-database” applied on the Teradata warehouseResults In 2 days KXEN built 10 production models that took 50 weeks to build with traditional modeling tools.Churn Analysis: InfiniteInsight® identified a group that is 3 times more likely to churn than the least likely identified group60 seconds to score 1,942,000 customers in the Teradata warehouseRevenue per Customer: InfiniteInsight® makes the model easier to understandQuality model improvement by 7 % over previously hand-crafted modelsCall Volume Analysis:model built in 2 minutes and 30 secondsApproved Quotes“We consolidate all the results of our analyses to define what we call each customer’s individual DNA. This shows us the likely evolution of that customer through their life with Belgacom in taking new products, in cancelling current products, or returning as a customer again” - Dr. Jacky Huyghebaert, Customer Intelligence Expert at Belgacom. Additional Quotes from 12/21/10 Press-release: “Time to market is precious.” - Jacky Huyghebaert“We needed a predictive analytics solution that would allow us to react quickly and efficiently. With InfiniteInsight®, we’ve cut modeling time from three months to only two to three days.” - Jacky Huyghebaert “Before InfiniteInsight®, we had to spend hours preparing data from our data warehouse into a format we could use. It wasn’t the best use of our time. Worst still, it was prone to human error.” - Jacky Huyghebaert “With InfiniteInsight®, we can deliver the right offer, to the right customer at the right time. It’s a real competitive advantage. We’re getting the most out of our marketing dollars and a higher return on our marketing investments.” Jacky Huyghebaert “People often think predictive analytics is overly complex. You need months to build a model and then weeks to deploy the results.” - Jacky Huyghebaert
  • KXEN Helps Monetize Their Social Networking Community

San Francisco, March 27, 2013 doubles the number of ‘friend requests’ and their corresponding rate of acceptance using KXEN’s InfiniteInsight® Recommendation
KXEN, the leading provider of predictive analytics for business users, today announced that, one of the leading social sites in Europe, has successfully deployed KXEN’s InfiniteInsight® Recommendation to improve stickiness and social engagement for its more than 18 million monthly visitors. 

“We’re ecstatic with the results we’ve achieved thanks to KXEN,” said Rémi Kirche, Marketing Director at “KXEN’s InfiniteInsight® Recommendation is giving us the ability to offer our members new services which have boosted engagement and overall site stickiness. Best of all, results with KXEN have been consistent over the past year, giving a real competitive advantage to our company.” is one of the fastest growing social network sites in the world, offering its members a free, personal web space to create blogs, add a profile, and exchange messages with other registered members. To assist in monetizing the site’s rapid growth, made a strategic decision to improve their member’s overall experience which would increase site stickiness and provide more valuable advertising impressions.

To achieve this objective, standardized on KXEN’s InfiniteInsight® Recommendation, which, unlike traditional recommendation engines, analyzes massive amounts of Big Data to provide personalized recommendations, such as products, friends, content (like blog posts) and targeted ads, to each unique visitor. Big Data is valuable to companies like, because it unlocks new sources of information that organizations could only dream of 5 years ago and can greatly increase prediction accuracy. uses InfiniteInsight® Recommendation to analyze the volumes of Big Data collected on their website, including: 

• Over 1 billion page views per month
• 1.4 million new comments daily
• 1 million “thumbs up” daily
• 1.8 million messages daily
• Over 10 TB of monthly data

“KXEN is committed to helping e-Businesses like gain unparalleled insight about their members,” said John Ball, CEO of KXEN. “We believe that personalized recommendations are critical for today’s e-Business to drive monetization of their websites.”

Friend Recommendation
As a social site where content is viewed and shared between members, uses InfiniteInsight® Recommendation to offer a list of 20 relevant ‘friend’ recommendations each morning to its members. Using this strategy, has doubled the number of ‘friend’ requests and their corresponding rate of acceptance. On average, sees more than 600,000 new ‘friend’ links each day.

Member Insight and Personalization also uses KXEN’s InfiniteInsight® to better understand individual users and identify communities with similar interests, characteristics and behaviors. Through InfiniteInsight®’s analysis, has detected 20,000 distinct communities such as shopping fans, horseback riders, new moms and car fanatics. is now piloting these results to recommend blog postings to visitors and members based on their profiles and tastes to further increase site stickiness. “These results opened our eyes on the power of customer data,” concluded Kirche.
For more information on KXEN and InfiniteInsight®, please visit:Website: http://www.kxen.comBlog: 
About is a social networking site that offers a free space on the web to allow its users to create blogs, add profiles, and exchange messages with other registered members. Founded in December 2002, was ranked a few years later as the world's seventh largest social network, and today counts more than 11 million registered users in France, 18 million distinct visitors and 1 billion page views every month, which places it among the top 10 sites in France, Belgium and Switzerland.
About KXEN
KXEN is revolutionizing the way companies use predictive analytics to make better decisions on petabytes of big data. Based on patented innovations, the company's flagship product, InfiniteInsight® and its pure cloud-based platform, Cloud Prediction™, delivers orders of magnitude improvements in speed and agility to optimize every step in the customer lifecycle – including acquisition, cross-sell, up-sell, retention and next best activity.  Proven with over 500 deployments at companies such as AAA, Allegro, Bank of America, Barclays, Belgacom, CBS Interactive, ING Direct, Lowe’s, Meredith Corporation, Mobilink,, PT XL Axiata, RealNetworks, Rhapsody, Rockwell, Rogers, Sears, Shutterfly, Stage Stores, U.S. Cellular and Vodafone, KXEN solutions deliver predictive power and infinite insight. KXEN is headquartered in San Francisco, California with field offices in the U.S., Paris and London.
  • Self-service data accessNative source accessData wranglingMore magic
  • Doctors perform surgery on the wrong body part about 40 times a week
  • Sources:Gartner MQ, BI Platforms, January 2011Forrester Wave, BI Platforms, October 2010Gartner MQ, CPM Suites, March 2011Gartner MQ, Data Integration Tools, October 2011Gartner MQ, Data Quality Tools, July 2011Gartner MQ, Data Warehouse Database Management Systems, January 2011Gartner MQ, Enterprise GRC, July 2011
  • Top Analytic Trends

    1. 1. Top Analytic Trends Timo Elliott, SAP Innovation Evangelist @timoelliott
    2. 2. © 2014 SAP AG. All rights reserved. 2 More, More, More
    3. 3. © 2013 SAP AG. All rights reserved. 3 #1
    4. 4. © 2014 SAP AG. All rights reserved. 4 Process data Human data Machine data
    5. 5. © 2014 SAP AG. All rights reserved. 5Source: Forrsights Strategy Spotlight: Business Intelligence And Big Data, Q4 2012 Unstructured 50TB Semi- structured 2 TB Structured 12 TB Only 12% used today Average data volume per company 9 TB 75 TB 0.6 TB 5 TB 4 TB 50 TB SMBs: LEs: Base: 634 business intelligence users and planners Companies don’t use most of their data
    6. 6. © 2014 SAP AG. All rights reserved. 6 What Is “Big Data”? The Google Summary
    7. 7. © 2014 SAP AG. All rights reserved. 7 Big Data is at Peak of Inflated Expectations… Source: Gartner
    8. 8. © 2014 SAP AG. All rights reserved. 8 Datification 0101101100010101010 1010010101001111010 1010100101110101010 1010101001001010010 0100101110110101010
    9. 9. © 2014 SAP AG. All rights reserved. 10 The Datification of Tennis
    10. 10. © 2014 SAP AG. All rights reserved. 12 The Datification of Cars
    11. 11. © 2014 SAP AG. All rights reserved. 13 The Datification of Cars
    12. 12. © 2014 SAP AG. All rights reserved. 14 The Datification of Cars
    13. 13. © 2014 SAP AG. All rights reserved. 15
    14. 14. © 2014 SAP AG. All rights reserved. 17 The Datification of Airports
    15. 15. © 2014 SAP AG. All rights reserved. 20 The Datification of Beer
    16. 16. © 2014 SAP AG. All rights reserved. 21
    17. 17. © 2014 SAP AG. All rights reserved. 22 “Data-driven decision making played a huge role in creating a second term for the 44th President. In politics, the era of big data has arrived.” - Time Magazine The Datification of Politics
    18. 18. © 2014 SAP AG. All rights reserved. 23 Analytics is Part of the Customer Experience
    19. 19. © 2014 SAP AG. All rights reserved. 24 i i i Business ownership IT ownership HBR: “Analytics 3.0” Information becomes what you sell
    20. 20. © 2014 SAP AG. All rights reserved. 25 The #1 Use of Big Data is Customer Analytics Source: McKinsey
    21. 21. 26© 2014 SAP AG or an SAP affiliate company. All rights reserved. CUSTOMER SPOTLIGHT L’Oréal • Be a trusted advisor for customers
    22. 22. © 2014 SAP AG. All rights reserved. 28 Experience Intelligence Center Event Interception Business Transformation Make People Happy
    23. 23. © 2014 SAP AG. All rights reserved. 29 Make People Happy
    24. 24. © 2014 SAP AG. All rights reserved. 30 Enterprise Operating Systems
    25. 25. © 2014 SAP AG. All rights reserved. 31 SMAC-down! (Social, Mobile, Analytics, Cloud) “Every business is an information business”
    26. 26. © 2014 SAP AG. All rights reserved. 32 Analytics Moves To The Core
    27. 27. © 2014 SAP AG. All rights reserved. 33 Enterprise “Data Lakes” and “Data Hubs”
    28. 28. © 2014 SAP AG. All rights reserved. 38 Hadoop Expands Data Warehouse Rather Than Replacing It Source: Gartner
    29. 29. © 2014 SAP AG. All rights reserved. 39 Big Data Enterprise Data Warehouses
    30. 30. © 2014 SAP AG. All rights reserved. 40 Perfect Your Pricing and Packaging
    31. 31. © 2014 SAP AG. All rights reserved. 41 Data Warehouse? Yes, But “Logical”
    32. 32. © 2014 SAP AG. All rights reserved. 42 Imagine if Your Apps Looked Like a DW to BI Tools SAP HANA SAP HANA Live (Virtual Data Model) Customer Service Risk Management Team Finance and Operations Account Administration Executive Management Customers Channel Suppliers Accounting ForecastingInventory Products Pricing Planning
    33. 33. © 2014 SAP AG. All rights reserved. 43 Here Comes HTAP
    34. 34. © 2014 SAP AG. All rights reserved. 44 Information Capability Framework
    35. 35. © 2014 SAP AG. All rights reserved. 45 Big Data Platforms
    36. 36. © 2014 SAP AG. All rights reserved. 46 SAP HANA Data Platform SAP Real-time Data Platform MPP Scale-Out 3rd Party BI Client SAP NetWeaver (On Premise / Cloud) Custom Apps SAP Business Suite SAP Business Warehouse SAP Big Data Applications SAP Analytics SAP Mobile Open Developer APIs and Protocols CommonLandscapeManagement SAP HANA PlatformSAP Sybase ASE CommonModeling SybasePowerDesigner HADOOP 3rdPartyDB SAP Sybase SQLA SAP Sybase ESP SAP Sybase IQ SAP Smart Data Services Platform SAP Sybase Replication Server SAP Data Services SAP MDG, MDM SAP SLT
    37. 37. © 2014 SAP AG. All rights reserved. 48 Governed Data Discovery
    38. 38. Wikipedia Local experts Encyclopedia Britannica Encarta Collective Insight Analogy – Encyclopedias
    39. 39. © 2014 SAP AG or an SAP affiliate company. All rights reserved. 51Public SAP Lumira Data Discovery
    40. 40. © 2014 SAP AG. All rights reserved. 57
    41. 41. © 2014 SAP AG. All rights reserved. 58 Location
    42. 42. © 2014 SAP AG. All rights reserved. 59
    43. 43. © 2013 SAP AG. All rights reserved. 60 Custom Visualization With Lumira
    44. 44. © 2014 SAP AG. All rights reserved. 61 Three Dimensions
    45. 45. © 2014 SAP AG. All rights reserved. 62
    46. 46. © 2014 SAP AG. All rights reserved. 63 Predictive For All
    47. 47. Descriptive: What happened? Diagnostic: Why did it happen? Predictive: What will happen? Prescriptive: How can we make it happen? Predictive reaches maturity Hindsight Insight Foresight
    48. 48. © 2014 SAP AG. All rights reserved. 65 The Chauffeur Effect
    49. 49. © 2014 SAP AG. All rights reserved. 66 Deliver The Right Offer To the Right Customer At The Right Time Modeling time from 3 months to 3 days Up to 4x increase in campaign response rates From product to customer marketing
    50. 50. © 2014 SAP AG. All rights reserved. 67 Skyrock: Social Network Skyrock blogs is the world's 7th largest social network with 18M visitors and 1B page views every month Friends recommendations of based on likes Content recommendations Banner personalization based on clicks
    51. 51. © 2014 SAP AG. All rights reserved. 68
    52. 52. © 2014 SAP AG. All rights reserved. 71 Data Inte gration and Qwality Is Still The Big Problem
    53. 53. © 2014 SAP AG. All rights reserved. 72 Edward James Snowden Edward Joseph Snowden
    54. 54. © 2014 SAP AG. All rights reserved. 73
    55. 55. © 2014 SAP AG. All rights reserved. 74
    56. 56. © 2014 SAP AG. All rights reserved. 75 Advanced Profiling Redundancy Profiling  Address Profiling  Validate address data  Dependency Profiling  Identify attribute-level connections in data. (Normalization rules practice)  Redundancy Profiling  Identify degree of duplication  Uniqueness Profiling  Identify non-unique data Drill down to duplicate and non-duplicate records
    57. 57. © 2014 SAP AG. All rights reserved. 76 Using Analytics To Track Data Quality Data quality score metrics Latest quality score Quality trend over time / run Key Quality Dimensions (KPI for data), customizabl e
    58. 58. © 2014 SAP AG. All rights reserved. 77 Data Wrangling and Self-Service ETL
    59. 59. © 2014 SAP AG. All rights reserved. 78 The New Analytics Governance
    60. 60. © 2014 SAP AG. All rights reserved. 79 Third-Generation BI Competency Centers
    61. 61. © 2014 SAP AG. All rights reserved. 80 You Are Being Watched Big Data Without Big Brother
    62. 62. © 2014 SAP AG. All rights reserved. 81 The Analyst View
    63. 63. © 2014 SAP AG or an SAP affiliate company. All rights reserved. 82Public Forrester Wave: Enterprise BI Platforms, Q4 2013 Strong proof point of SAP’s leadership in the BI market SAP finished strongly across Strategy, Current offering, and Market presence  #1 on Strategy – on par with Microsoft  Slightly behind IBM for Current offering  Top market presence with IBM & MSFT SAP moved up and right significantly in comparison to the previous Enterprise BI Platforms Wave dated from Q4 2010 SAP leads the market with broad BI innovations 1 2 3
    64. 64. © 2014 SAP AG or an SAP affiliate company. All rights reserved. 83Public Forrester Wave: Big Data Predictive Analytics Solutions, Q1 2013 SAP also differentiates by putting its SAP HANA in-memory appliance at thecenter of its offering SAP finished strongly across Strategy and Current offering  #1 on Strategy – on par with IBM and SAS  Slightly behind IBM and SAS for Current offering SAP showed up strongly for first time and #3 vendor in this space. Newcomer SAP performs well 1 2 3
    65. 65. © 2013 SAP AG. All rights reserved. 84 Gartner BI & Analytics a Gartner CPM Suites Forrester ADV b Forrester Self- Service BI c Forrester Big Data Predictive d Gartner Analytics Market Share e SAP 1 Oracle 2 IBM 3 SAS 4 Microsoft 5 MicroStrategy 6 QlikTech 7 Information Builders 9 TIBCOSpotfire 10 Tableau Software 13 Notes 1. General criteria for inclusion: Vendor must have either a Leader or Challenger rating or be rated in more than one Magic Quadrant Sources Gartner - “Magic Quadrant for BI & Analytics Platforms” – Feb 2013; b. Forrester – “Forrester Wave: Advanced Data Visualization Platforms, Q3 2012” – Jul 2012; c. Forrester Wave: Self Service BI Platforms, Q2 202” – Jun 2012; d. Forrester – “Forrester Wave: Big Data Predictive Analytics Solutions, Q1 2013” – Jan 2013; e. Gartner - “Market Share Analysis: Business Intelligence, Analytics and Performance Management, 2012” – May 2013 Leader Strong Performer
    66. 66. © 2014 SAP AG. All rights reserved. 85 Conclusion
    67. 67. © 2014 SAP AG. All rights reserved. 86 Thank you! Timo Elliott, SAP Twitter: @timoelliott Blog: