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UKISUG Top Big Data & Analytics Trends

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Presentation delivered at the UK & Ireland SAP User Group (UKISUG) Special Interest Group meeting for Big Data & Analytics

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UKISUG Top Big Data & Analytics Trends

  1. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 1 Big Trends in Big Data & Analytics Timo Elliott VP, Global Innovation Evangelist AKA “What I personally find interesting”
  2. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 2 Congratulations! YOU WON
  3. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 3 88% How Do Executives Make Decisions? Aspect Consulting, 1997 12% Hard Facts Gut Feel 90% 10% Hard Facts Gut Feel Economist Intelligence Unit, 2014 Why the worst-practice shaded 3D donut charts? JUST TO ANNOY DATA VIZ EXPERTS! 
  4. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 4 Biggest Barriers to Business Intelligence 51% 48% 44% Data Quality Problems Ease of Use Integration of different systems 43% 37% 36% It is difficult to determine if information is accurate It takes a long time to find information Information is stored in ways that makes it hard to find 20152003 Sources: InformationWeek Survey 2015, BusinessWeek Survey, 2003
  5. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 5 Business Intelligence Success… Sources: InformationWeek Survey 2015, BusinessWeek Survey, 2003 41% 53% 35% Disagree Disagree somewhat Agree somewhat Completely agree 2012 2013 2014 2015 ?
  6. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 6 The Opportunity Inability to see, understand, and optimize new opportunities Inaccessible data and technology Insights remain hidden Complexity, cost, confusion Silos of approaches and analytic technologies Slow decision making lacking future view Rear view mirror BI mentality
  7. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 7 cloud data mobile MORE! competition speed social connected There’s Been An Explosion of New Technology Means new opportunities…
  8. 8© 2015 SAP SE or an SAP affiliate company. All rights reserved. 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
  9. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 9 New Products & Services
  10. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 10 The Opportunity New Business Opportunities Traditional Analytics Data Value Volume / Variety / Velocity of Data “Big Data Discovery” Data Discovery Big Data Data Science
  11. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 11 SAP’s Opportunity Big Data Discovery SAP HANA (+ Hadoop etc.) SAP Predictive Analytics 2.0 SAP Lumira
  12. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 12 The Landscape is Converging
  13. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 13 May Imply Differently Sliced Products? Big Data Discovery Basic Big Data Discovery Team ETL BI Q&R OLAP Predictive Big Data Discovery Advanced Example only — not a product plan!
  14. Boardroom Redefined Source: In-Memory Data Management: An Inflection Point for Enterprise Applications. Hasso Plattner Alexander Zeier
  15. 15© 2015 SAP SE or an SAP affiliate company. All rights reserved. “Intricate calculations of sales by territories will appear as if by magic in the digital age ahead”
  16. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 16 Decision Cockpits
  17. 17© 2015 SAP SE or an SAP affiliate company. All rights reserved.
  18. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 18 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. • 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 “In-memory cannot economically, or even practically, scale to the volumes of today’s data warehouses — Neil Raden, 2012”
  19. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 19 Mercy Health Mercy Named One of Nation’s Most Wired for 11th Year 40K employees, >8M patients/year, 9 years of data, structured & unstructured
  20. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 20 Hadoop Rising (?) 8.5 22.8 -20.3 -40.1 1Q 2014 1Q 2015 587 670 666 769 628 676 667 761 582 1Q 2013
  21. 21© 2015 SAP SE or an SAP affiliate company. All rights reserved. SAP, Open Source & Hadoop 1 10 100 1000 10000 Open source consumption Open source contribution SAP Contributes to over 100 Open Source Projects
  22. SAP HANA Platform Bringing Enterprise Data to Hadoop and Hadoop Data to The Enterprise SPATIAL PROCESSING ANALYTICS, TEXT, GRAPH, PREDICTIVE ENGINES CONSUME COMPUTE STORAGE SOURCE INGEST Application Development Environment Transformations & Cleansing Smart Data Integration Smart Data Quality Stream Processing Smart Data Streaming STREAM PROCESSING LogsTextOLTP Social MachineGeoERP SensorStore & forward Mobile applications and BI Smart Data Access Virtual Tables User Defined Functions 1010100 1010110 1001110 Dynamic Tiering Aged data in Disk In-Memory Data model & data Calculation engine Fast computing Column Storage High performance analytics Series Data Storage Store time- series data Reporting & Dashboards High Performance Applications Data Exploration & Visualization Adhoc & OLAP Analytics Predictive Analysis Business Planning & Forecasting Lumira / BI But there is more work to do… Hadoop / NoSQL MapReduce YARN HDFS
  23. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 23 The New Multi-Polar World of Big Data Architectures Data Warehouse Hybrid Transaction/ Analytical Processing Hadoop, MongoDB, Spark, etc Personal Data / BI Where does data arrive? When does it need to move? Where does modeling happen? What can users do themselves? What governance is required? Big Data Architectures got complicated What we want — consistent, seamless solution
  24. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 24 Apache Atlas
  25. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 25 Data Preparation is a Highly Iterative and Time-consuming Process Commonly accepted that ~80% of the work on data analytics is in preparation
  26. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 26 Self-service Data Preparation Tools Reduce the Time and Complexity of Preparing the Data Source: Gartner Gartner predicts by 2018 most business users will have access to self-service tools to prepare data for analytics
  27. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 27 SAP Agile Data Preparation: Cleanse
  28. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 28 SAP Agile Data Preparation: De-Duplicate
  29. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 29 SAP Agile Data Preparation: Merge
  30. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 30 SAP Agile Data Preparation: Admin
  31. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 31 SAP Agile Data Preparation: Operationalize Export Action History and Import as a flowgraph in HANA EIM
  32. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 32 Data Visualization is Cool… (but) Not using pie charts Ease of use, training, data quality, incentives, organization, process, etc. etc. Importance for BI Success of:
  33. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 33 We Still Need Reporting and Dashboards! 18% 19% 25% 35% 53% 69% Query & Analysis Data Discovery Alerts Dashboards Reports Spreadsheets Source: InformationWeek BI Survey 2015 Question: “To what extent are the following technologies used to share analytic and BI insights within your organization?” and response: “Used Extensively”
  34. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 34 We Need To Support The Analytics Lifecycle
  35. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 35 Transport For London
  36. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 36 Centerpoint Energy
  37. DATA SCIENCE QUIZ. These numbers were found in two tax declarations. One is entirely made up. Which one? EUR 127,- 2.863,- 10.983,- 694,- 29.309,- 32,- 843,- 119.846,- 18.744,- 1.946,- 275,- EUR 937,- 82.654,- 18.465,- 725,- 98.832,- 7.363,- 4.538,- 38,- 8.327,- 482,- 2.945,- Benford's Law, also called the First-Digit Law
  38. 30.1% 17.6% 12.5% 9.7% 7.9% 6.7% 5.8% 5.1% 4.6% 1 2 3 4 5 6 7 8 9 Benford’s Law Distribution of the first digit of real-world sets of numbers that uniformly span several orders of magnitude
  39. 39© 2015 SAP SE or an SAP affiliate company. All rights reserved. 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, 2011
  40. Repeat purchases A B Big Data looks Beyond Sales of two new products six weeks after market introduction
  41. 41© 2015 SAP SE or an SAP affiliate company. All rights reserved. Kaeser Compressors Enabling Predictive Maintenance A global leader in air compressors ≈€500 million, 4,800 employees, 50 countries, partners in additional 60 countries
  42. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 42 Benefits Customers • Less downtime • Decreased time to resolution • Optimal longevity and performance Kaeser • More efficient use of spare parts, etc • New sales opportunities • Better product development “We are seeing improved uptime of equipment, decreased time to resolution, reduced operational risks and accelerated innovation cycles. Most importantly, we have been able to align our products and services more closely with our customers’ needs.”• Kaeser CIO Falko Lameter Next Steps: New Business Models
  43. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 43 SAP HANA Cloud Platform - the Internet of Things enabled in-memory platform-as-a-service Machine Cloud (SAP) HANA Cloud IoT Services End Customer (On site) Business owner (SAP Customer) HANA Cloud Integration Business Suite Systems (ERP, CRM , etc.) SAP ConnectorDevice HANA Big Data Platform Data Processing Extended Storage Hadoop In-Memory Engines Streaming Storage ∞ HANA Cloud Platform Machine Integration Process Integration IoT Applications (SAP, Partner and Custom apps)
  44. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 44 SIEMENS Cloud for Industry The SIEMENS ‘Cloud for Industry’ connects the worlds of machines and business via: • the HCP for IoT • open APIs • easy connectivity. It is the successor of the SIEMENS Plant Data Services. It is planned to be an open platform: • Open to non-Siemens assets and non- SAP back-ends • Endorsing the OPC UA Standards • Creating a separate, yet adjacent & complementary partner developer network R&D Sales Manufacturing Aftermarket Service Supply Chain In-Memory Cloud Platform for the Internet of Things Partner Connectivity Customer Connectivity SAP Connectivity SIEMENS Connectivity Partner Applications Customer Applications SAP Applications SIEMENS Applications Machine connectivity to SIEMENS customers plants Business Process Integration (SIEMENS or SIEMENS customers) Cloud for Industry
  45. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 45 Tweeting Sharks!
  46. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 46 Drones
  47. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 47 Time to Reach For The Clouds?
  48. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 48 Finance & Analytics: It’s Déjà Vu All Over Again CloudAny Device Social Collaboration Big Data Enterprise Performance Management Governance, Risk, and Compliance Discover Inform Anticipate Plan Business Intelligence Predictive Analytics Real-time Business
  49. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 49 Is This Your Finance Team? "With 90% certainty, here’s where we closed last month…"
  50. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 50 Finance wants to be a business partner. And that requires better, more forward- looking data.
  51. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 51 Planning For The Rest of Us
  52. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 52 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. 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 45% 55% In enterprise systems Not in enterprise system
  53. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 53 Advanced Governance Central IT no longer has a veto — you need the “consent of the governed” This means you have to behave more like a politician…
  54. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 54 Build and Nurture a Community Regular face-to-face meetings • Bring people together across silos: IT, Analysts, Business Leaders, Execs • Presentations of successes best practices • Invite external speakers Virtual communities • Leverage internal social tools for people to share information • Community-driven BI content Community self-policing • Act as BICC eyes and ears to discover projects, opportunities • Social mechanisms to ensure the “right behaviors” Ensure support at all levels • Not just executives — middle and users
  55. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 55 Conclusion: There’s a LOT Going On in Analytics • Big data discovery • The boardroom redefined • SAP HANA & Hadoop • Multi-polar big data architectures • Self-service data preparation • Supporting the analytics lifecycle • Prescriptive and predictive analytics • Internet of things for business • Finance and analytics converge (again) • Analytics culture & governance
  56. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 56 “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
  57. Thank You! Timo Elliott VP, Global innovation Evangelist Timo.Elliott@sap.com @timoelliott timoelliott.com/docs/UKISUG_top_analytic_trends.zip

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