Business Agility Must Be Based on a New Flexible and Agile Data Approach

1. © 2015 Denodo Craig LeClaire VP, Principal Analyst Megan Burns VP, Principal Analyst Cory Munchbach Analyst Holger Kisker, Ph.D. VP and Research Director Session 1 CIO’s Must Enable Business Agility via Modern Data Management in the Age of the Customer Session 2 Understanding the Customer Experience Ecosystem to Succeed in the Age of the Customer Session 3 Build a Contextual Marketing Engine and Fuel it with Data Session 4 Business Agility Must Be Based on a New Flexible and Agile Data Approach Data Virtualization for Business Intelligence and Business Agility in the Age of the Customer Four sessions providing insights and best practices for the Age of the Customer WEBINAR SERIES featuring FORRESTER RESEARCH

4. Making Leaders Successful Every Day

5. Business Agility Must Be Based on a New Flexible and Agile Data Approach Holger Kisker, Ph.D. Vice President & Research Director

6. Data initiatives are the most important tech investments Source: Forrsights Software Survey, Q4 2013 Base: 2,074 technology executives and technology decision makers 57% of decision makers rank data projects the most important investment in their company 7% 16% 15% 18% 20% 24% 5% 12% 18% 17% 16% 33% Social related projects Mobile related projects Cloud related projects Systems of engagement applications Systems of record applications Data related projects 2nd Priority Top Priority Please rank the following technologies according to their importance and investment within your firm?

7. © 2013 Forrester Research, Inc. Reproduction Prohibited 7 The main driver is to better decisions What are the most important goals/drivers your organization considers when planning or orchestrating your business intelligence strategy? 10% 21% 27% 28% 29% 37% 42% 43% 53% Achieve better business transparency Develop better products and services Improve business planning Gain competitive advantage Ensure compliance and reduce risks Improve data quality and consistency Improve customer interaction and satisfaction Monitor, improve, and optimize process performance Make better informed business decisions Base: 249 North American business decision-makers Respondents answering “don’t know” are not shown Source: Global Data and Analytics Survey, 2014 Business growth drivers Technical & control drivers

8. Turn Data Into Business Insights More Deeper For Everyone

9. Deeper Insights More Data For Everyone

10. © 2014 Forrester Research, Inc. Reproduction Prohibited Culture • Data treated as an asset • Data-driven • Data shared across silos Capabilities • Advanced data management, delivery and analysis Competency • Technology skills • Analytical skills • New approach to data governance • Agile processes Success Ingredients To A New Flexible And Agile Data Approach

11. © 2014 Forrester Research, Inc. Reproduction Prohibited Culture • Data treated as an asset • Data-driven • Data shared across silos Competency • Technology skills • Analytical skills • New approach to data governance • Agile processes Capabilities • Advanced data management, delivery and analysis Success Ingredients To A New Flexible And Agile Data Approach

12. © 2014 Forrester Research, Inc. Reproduction Prohibited Choose The Appropriate Data Management Technology Highlytopolystructured Batch to real time Velocity Variety Scalable NoSQL In-memory Streaming Standard SQL apppliance Structured historical data Int./ext. polystructured data In-time dynamic data Real-time data in motion

14. © 2014 Forrester Research, Inc. Reproduction Prohibited Data Science Workbench Hadoop Streaming SQL Datawarehouse Application In-Memory Datawarehouse Any Data Sources A new approach to architecture – hub-and-spoke (example)

15. Advanced data analytics for deeper Insights Advanced data management technologies to use more data Advanced data delivery technologies to leverage & share insights

16. © 2014 Forrester Research, Inc. Reproduction Prohibited Data About The Future Is The Most Valuable! 10% 14% 13% 15% 14% 18% 18% 23% 18% 21% 28% 29% 37% 31% 27% 28% 31% 5% 7% 8% 7% 10% 8% 12% 11% 17% 15% 22% 22% 26% 36% 41% 44% 53% Unstructured external data Social network data Consumer mobile device data Weblog data from publically facing sites Sensor data other than mobile devices Video, imagery & audio Partner data Third party data sets Scientific data Log data from corporate systems Product data Unstructured internal data Home-grown data stored in spreadsheets or other… Transactional data from corporate custom build apps Customer data Transactional data from corporate packaged apps Planning, budgeting, forecasting data 4 5. very important Base: 634 Business Intelligence users and planners “How important are the following data types to your firm's overall business strategy?” Answers 4 and 5 on a scale where 1- not at all important and 5 – very important Source: Forrsights BI/Big Data Survey, Q3 2012 Data value $$

18. You know nothing about your customer

19. Deeper Customer Insights With Advanced Analytics Why did he buy our product? What is he going to need next?When will he need support? Where is he right now?

20. Advanced data analytics for deeper Insights Advanced data management technologies to use more data Advanced data delivery technologies to leverage & share insights

21. © 2014 Forrester Research, Inc. Reproduction Prohibited Visual display and self-service are key Image source & copyright: http://www.cloudred.com/labprojects/nyctrees/ Image source & copyright: Microsoft

23. © 2014 Forrester Research, Inc. Reproduction Prohibited New hub-and-spoke architecture Data Science Workbench Hadoop Streaming SQL Datawarehouse Application In-Memory Datawarehouse Any Data Sources

24. © 2014 Forrester Research, Inc. Reproduction Prohibited How Much Hadoop Skills Do You Need? Very few specific skills: Using „enterprise-ready“ Hadoop solutions, (e.g. MapR, Cloudera, Hortenworks) Some specific skills: Leverage OpenSource Ecosystem (e.g. Pig, Hive, HBase) Native Hadoop integration: Java coding in distributed file system with map-reduce

25. © 2014 Forrester Research, Inc. Reproduction Prohibited › Advanced analytics apply data models based on mathematic-statistical methodologies & algorithms • What is the right algorithm? • Adjust the model to reflect business reality Data Scientist: Sexiest Job of the 21st Century › Vendors start to close the skills gap with pre- packaged solutions and data services › A team-based approach is essential: tech management & data scientist & business & other experts

26. Source: http://www.practicaldb.com/demos/ Build Integrate UseShare Self- Service Skills & Processes

28. © 2014 Forrester Research, Inc. Reproduction Prohibited Business outcome Data sources Deeper insights More data For everyone What business value do we want? Who needs what insights for this? What analysis tools do we need? How can we manage all the data needed? What data do we have? How can we process that data? What can we learn from this data? How do we deliver those insights? Bottom-uptechnology-driven Top-downbusiness-driven What business value can we create? What data sources do we need? There’s no single right way to plan

29. Data delivers benefits on different levels Strategic Benefits (e.g. increased asset value on balance sheet, reduced risk exposure, improved performance, better planning) LoB Benefits (e.g. downtime, operational cost, asset utilization, improved quality, production performance) User Benefits (e.g. decision support, reduced search time, satisfaction, self-service, mobile support) IT Benefits (e.g. data quality, data utilization, improved models, real-time, improved SLAs) „Data Will Become An Asset On The Balance Sheet“

30. © 2014 Forrester Research, Inc. Reproduction Prohibited Everybody can benefit from big data Base: 1,077 North American and European Software decision-makers who are using or Planning to use big data (20+ employees) “What groups or departments are currently using big data/planning to use big data in 2014?” Source: Forrester’s Forrsights Software Survey, Q4 2013 Operations 38% (e.g., supply-demand) Marketing 34% (e.g., campaigns) IT analytics 58% (e.g., network secure) Finance 31% (e.g., risk exposure) Sales 36% (e.g., cross-/upsell) Research 32% (e.g., simulation) Customer service 31% (e.g., segmentation) Manufacturing 20% (e.g., process opt.) GRC 14% (e.g., auditing) Product development28%(e. g., social feedback) Logistic and distr. 27% (e.g., route opt.) Human resources 19% (e.g., head hunting) Procurement 17% (e.g., best buy) Supply chain 23% (e.g., sourcing) Other 3% Don’t know 1%

31. Hadoop Reporting Process Optimization Data Management Data Processing Information Usage Data Sources EDW Advanced Analytics Decision Support Engagement Systems of Customer Engagement In-Memory Streaming Record Systems of Economy Data

35. Hadoop EDW Streaming Engagement Systems of Record Systems ofReporting Advanced Analytics Customer Engagement Economy DataDecision Support Process Optimization In-Memory Data Management Data Processing Information Usage Data Sources

36. Data Sources Data Virtualization Data Virtualization Discovery Access Manage Monitor Performance

37. Data Sources Data Virtualization Manage Unified Data Governance • Security • Privacy • Quality • Standards • Life Cycle Access Unified Data Access to any • Source • Application • Insight • Employee • Customer • Business Partner Monitor Unified Data Monitoring • BI on BI • Compliance • Health • Business Usage Discovery Finding the nuggets • Sources • Pattern • Insights • Use Cases • Business Value Performance Optimized Data Performance • Workload Optimization • Cost • Availability • Usability • Business Managing the Complexity Of A Modern Data Architecture

38. Image source: Big Data World Congress (http://bigdatacongress.com/) and c1.staticflickr.com ((//c1.staticflickr.com/1/40/123900378_e668dd966e.jpg)

39. There is no single ‘best’ data Use Case; start your own road map. There is no single ‘best’ data technology; see what fits your needs. Don‘t create data silos; think strategically and put in place a flexible platform & data virtualization Tech management recommendations

40. Thank you Holger Kisker hkisker@forrester.com @hkisker +49 69 959 29862

41. © 2015 Denodo CDO / CIO new calling - Turn MORE data into DEEPER business insights for EVERYONE Requires new capability, competency and culture of data as an asset Capabilities at 3 levels of data, analytics, delivery of insights requires variety of best of breed tools Beware of increased complexities , solution silos, replicated data, Big Data Zoo! Agile data architecture across layers - data source, management, processing, delivery – to abstract, hide complexity, deliver info faster Forrester Take Aways Denodo Enablers Fast data access; Information-as-a- service; Agile integration Organize canonical business entities used across dimensions Single View of Customer; Data distribution across channels Structured & unstructured; Internal & external; Real-time; Self-Service; Less replicated; Virtual Unified data abstraction layer democratizes access to single source of truth across and beyond organization boundaries Agile Data Architecture – How Denodo drives it

42. © 2015 Denodo  Access any source  Make them look homogeneous  Pre-integrated graph of information for users  Build very rapidly  Data services feed many applications & users ROI? “..saved 1000s of development hours” “.. exceeded breakeven expectations – smash through it!” “.. tackled business value for more leverage, not IT cost” Agile Data Architecture – Capital Markets Firm

44. © 2015 Denodo Data Virtualization - Two Approaches to Adopt Solve one/more projects Prove value Expand to other use cases Reusability and scalability Expand enterprise- wide Enterprise strategic vision Design for scale and support Systemic data services High value use cases first Multiple usage patterns Tactical Approach Enterprise-wide Approach People Process Technology Hybrid Approach Possible

46. © 2015 Denodo Thank you! Data Virtualization for Business Intelligence and Business Agility in the Age of the Customer Four sessions providing insights and best practices for the Age of the Customer WEBINAR SERIES featuring FORRESTER RESEARCH

Business Agility Must Be Based on a New Flexible and Agile Data Approach

Business Agility Must Be Based on a New Flexible and Agile Data Approach

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