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1 Timo Elliott VP, Global Innovation Evangelist 2015 SAP SE or an SAP affiliate company. All rights reserved. 1

2 Analytics Takes Over The World 2015 SAP SE or an SAP affiliate company. All rights reserved. 2

3 How Do Executives Make Decisions? Aspect Consulting, 1997 Economist Intelligence Unit, % Hard Facts 10% Hard Facts 88% Gut Feel 90% Gut Feel Why the worst-practice shaded 3D donut charts? JUST TO ANNOY DATA VISUALIZATION EXPERTS! 2015 SAP SE or an SAP affiliate company. All rights reserved. 3

4 Plus Ça Change 2015 SAP SE or an SAP affiliate company. All rights reserved. 4

5 Big Data On The Gartner Hype Cycle Big Data In-Memory Analytics Innovation trigger Peak of Inflated Expectations Trough of Disillusionment Slope of Enlightenment Plateau of Productivity Source: Gartner, August SAP SE or an SAP affiliate company. All rights reserved. 5

6 Benefits from Big Data Initiatives #5 Identified new product opportunities (6%) #4 More reliable decision making (9%) #3 Improved operational efficiency (11%) #2 Identified new business opportunities (31%) #1 DON T KNOW (51%) Source: Information Difference Research Study Dec 2013: Big Data Revealed 2015 SAP SE or an SAP affiliate company. All rights reserved. 6

7 The Opportunity Use Analytics 10% Today Inaccessible data and technology Silos of approaches and analytic technologies Insights remain hidden Complexity, cost, confusion Rear view mirror BI mentality Slow decision making lacking future view Gartner, % Need Analytics by 2020 Inability to see, understand, and optimize new opportunities 2015 SAP SE or an SAP affiliate company. All rights reserved. 7

8 Predicting Prescriptive Analytics 2015 SAP SE or an SAP affiliate company. All rights reserved. 8

9 Taking Analytics To The Next Level Descriptive: What happened? Diagnostic: Why did it happen? Predictive: What will happen? Prescriptive: How can we make it happen? Hindsight Insight Foresight

10 Tweeting Sharks! 2015 SAP SE or an SAP affiliate company. All rights reserved. 10

11 Drones 2015 SAP SE or an SAP affiliate company. All rights reserved. 11

12 These numbers were found in two tax declarations. One is entirely made up. Which one? DATA SCIENCE QUIZ. EUR 127, , ,- 694, ,- 32,- 843, , , ,- 275,- EUR 937, , ,- 725, , , ,- 38, ,- 482, ,-

13 30.1% Benford s Law Distribution of the first digit of real-world sets of numbers that uniformly span several orders of magnitude 17.6% 12.5% 9.7% 7.9% 6.7% 5.8% 5.1% 4.6%

14 These numbers were found in two tax declarations. One is entirely made up. Which one? Benford's Law, also called the First-Digit Law DATA SCIENCE QUIZ. EUR 127, , ,- 694, ,- 32,- 843, , , ,- 275,- EUR 937, , ,- 725, , , ,- 38, ,- 482, ,-

15 1999 to 2009 Greece shows the largest deviation from Benford s law with respect to all measures. [And] the suspicion of manipulating data has officially been confirmed by the European Commission. Fact and Fiction in EU-GovernmentalEconomic Data, SAP SE or an SAP affiliate company. All rights reserved. 15

16 Transport For London 2015 SAP SE or an SAP affiliate company. All rights reserved. 16

17 Centerpoint Energy 2015 SAP SE or an SAP affiliate company. All rights reserved. 17

18 Finance & Analytics 2015 SAP SE or an SAP affiliate company. All rights reserved. 18

19 Finance & Analytics: It s Déjà Vu All Over Again Discover Any Device Predictive Analytics Governance, Risk, and Compliance Cloud Anticipate Real-time Business Plan Social Collaboration Business Intelligence Enterprise Performance Management Big Data Inform 2015 SAP SE or an SAP affiliate company. All rights reserved. 19

20 Is This Your Finance Team? "With 90% certainty, here s where we closed last month " 2015 SAP SE or an SAP affiliate company. All rights reserved. 20

21 Finance wants to be a business partner. And that requires better, more forwardlooking data SAP SE or an SAP affiliate company. All rights reserved. 21

22 Big Data Discovery 2015 SAP SE or an SAP affiliate company. All rights reserved. 22

23 Big Data = Discovery Big Data Data Discovery Data Science Gartner Strategic Planning Assumption: By 2017, Big Data Discovery Will Evolve Into a Distinct Market Category 2015 SAP SE or an SAP affiliate company. All rights reserved. 23

24 Big Data Discovery Volume, velocity, or variety of data Potential business impact Difficult to implement Potentially expensive Lack of skills available Ease of use Agility and flexibility Time-to-results Installed user base BIG DATA DATA DISCOVERY DATA SCIENCE Complexity of analysis Potential impact Range of tools Smart algorithms Difficult to implement Slow and complex Narrow focus of analysis Limited depth of information exploration Low complexity of analysis 2015 SAP SE or an SAP affiliate company. All rights reserved. 24

25 Big Data Discovery BIG DATA Simpler to use than data science Accessible to a wider range of users Broad range of data manipulation features Able to handle new types of data sources DISCOVERY With adequate performance for big data 2015 SAP SE or an SAP affiliate company. All rights reserved. 25

26 The Rise of the Citizen Data Scientist? Potential user base Citizen data scientist Potential impact per user Business analyst Data scientist 2015 SAP SE or an SAP affiliate company. All rights reserved. 26

27 Citizen Data Scientists 2015 SAP SE or an SAP affiliate company. All rights reserved. 27

28 The Opportunity Data Value Big Data Discovery Data Discovery Big Data Data Science New Business Opportunities Traditional Analytics Volume / Variety / Velocity of Data 2015 SAP SE or an SAP affiliate company. All rights reserved. 28

29 SAP s Opportunity SAP HANA (+ Hadoop etc.) Big Data SAP Predictive Analytics 2.0 Discovery SAP Lumira 2015 SAP SE or an SAP affiliate company. All rights reserved. 29

30 The Dashboards of Yesterday And Tomorrow 2015 SAP SE or an SAP affiliate company. All rights reserved. 30

31 Intricate calculations of sales by territories will appear as if by magic in the digital age ahead 2015 SAP SE or an SAP affiliate company. All rights reserved. 31

32 Decision Cockpits 2015 SAP SE or an SAP affiliate company. All rights reserved. 32

33 Boardroom Redefined Source: In-Memory Data Management: An Inflection Point for Enterprise Applications. Hasso Plattner Alexander Zeier

34 2015 SAP SE or an SAP affiliate company. All rights reserved. 34

35 The New Multi-Polar World of Analytics 2015 SAP SE or an SAP affiliate company. All rights reserved. 35

36 In-Memory Maturity e.g. Wal-Mart s Data Café ( Collaborative Analytics Facilities for Enterprise ) Data from 245M customers/week, 11,000 stores under 71 banners in 27 countries and e-commerce websites in 11 countries with $482.2 Bn sales and 2.2M employees. Full in-memory system 250 Bn rows of data 94% of queries run < 2s >1,000 concurrent users even under heavy loads Data load throughput >20 million records/hour Suja Chandrasekaran CTO of Walmart Technology 2015 SAP SE or an SAP affiliate company. All rights reserved. 36

37 The End of the Hadoop Honeymoon? Despite considerable hype and reported successes for early adopters, only 18% have plans to invest in Hadoop over the next two years. in fact, there are fewer who plan to begin in the next two years than already have. Nick Heudecker, research director at Gartner SAP SE or an SAP affiliate company. All rights reserved. 37

38 Bringing Enterprise Data to Hadoop and Hadoop Data to The Enterprise Mobile applications and BI CONSUME High Performance Applications Business Planning & Forecasting Reporting & Dashboards Adhoc & OLAP Analytics Data Exploration & Visualization Predictive Analysis Lumira / BI COMPUTE Application Development Environment SAP HANA Platform STREAM PROCESSING ANALYTICS, TEXT, GRAPH, PREDICTIVE ENGINES SPATIAL PROCESSING Hadoop / NoSQL In-Memory Calculation engine Column Storage Series Data Storage Dynamic Tiering STORAGE Data model & data Fast computing High performance analytics Store timeseries data Aged data in Disk MapReduce INGEST Smart Data Streaming Stream Processing Smart Data Access Virtual Tables User Defined Functions Smart Data Integration Smart Data Quality Transformations & Cleansing YARN HDFS SOURCE ERP OLTP Geo Store & forward Text Social Logs Machine Sensor But there is more work to do

39 The New Multi-Polar World of Big Data Architectures Data Warehouse Hadoop, MongoDB, Spark, etc Hybrid Transaction/ Analytical Processing Third-Party Data Feeds Personal Data / BI Big Data Architectures got complicated Where does data arrive? When does it need to move? Where does modeling happen? What can users do themselves? What governance is required? What we want consistent, seamless solution 2015 SAP SE or an SAP affiliate company. All rights reserved. 39

40 Strategic Advisory Services for Big Data 1 2 Capability Framework Strategy Summary Strategy Governance Architecture Processes & Functions Organization & Workforce 3 4 Target Architecture Transformation Map 2015 SAP SE or an SAP affiliate company. All rights reserved. 40

41 Apache Atlas 2015 SAP SE or an SAP affiliate company. All rights reserved. 41

42 Analytics Culture 2015 SAP SE or an SAP affiliate company. All rights reserved. 42

43 Business vs. Corporate IT: It s Not You It s Your Data We found, on average, that 45% of the data business people use resides outside of the enterprise BI environments. An astonishingly miniscule 2% of business decision-makers reported using solely enterprise BI applications. 55% 45% This is undoubtedly connected to 76% of business respondents indicating they continue to resort to spreadsheets and other homegrown BI applications to analyze BI data. Source: Forrester In enterprise systems Not in enterprise system 2015 SAP SE or an SAP affiliate company. All rights reserved. 43

44 Are you the taxi company, or Uber? 2015 SAP SE or an SAP affiliate company. All rights reserved. 44

45 Culture: Suits AND Hoodies Source: Gartner 2015 SAP SE or an SAP affiliate company. All rights reserved. 45

46 Conclusion Prescriptive Analytics Finance & Analytics Big Data Discovery Dashboards of Tomorrow Multi-Polar Analytics Analytics Culture 2015 SAP SE or an SAP affiliate company. All rights reserved. 46

47 Judge a man by his questions rather than his answers. Voltaire Status Quo is, you know, latin for the mess we re in Ronald Reagan Any intelligent fool can make things bigger and more complex. It takes a touch of genius and a lot of courage to move in the opposite direction. E.F. Schumacher 2015 SAP SE or an SAP affiliate company. All rights reserved. 47

48 Thank You! Timo Elliott VP, Global innovation

Timo Elliott VP, Global Innovation Evangelist. 2015 SAP SE or an SAP affiliate company. All rights reserved. 1

Timo Elliott VP, Global Innovation Evangelist. 2015 SAP SE or an SAP affiliate company. All rights reserved. 1 Timo Elliott VP, Global Innovation Evangelist 2015 SAP SE or an SAP affiliate company. All rights reserved. 1 Analytics Takes Over The World 2015 SAP SE or an SAP affiliate company. All rights reserved.

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