The 2012 Data Informed Analytics and Data Survey

Transcription

1 The 2012 Data Informed Analytics and Data Survey Table of Contents Page 2: Page 2: Page 4: Page 21: Page 36: Page 39 Introduction Who Responded? What They Want to Know What They Don t Understand Managing Data and Data Projects Big Data and Analytics Plans Page 1

2 Introduction In June, we invited thousands of business and IT professionals to answer questioned about their needs, knowledge, and plans regarding analytics and big data in their organizations. About 250 responded representing 23 industries with some surprising and not so surprising results. Who Responded? The first surprise of the survey is the mix of business vs. technical respondents. Business professionals responded out of proportion to the number invited to answer the survey (Figure 1). Three of the top four roles respondents identified themselves with business analyst, business manager, and executive management were focused on the business side, about 35% of the total respondents. This supports the notion that data is becoming the domain of the business rather than the IT side within the enterprise. A note about the categories: The verbatim responses about job titles and roles for people in the category suggest that many of these respondents are not representative of the audience we wanted to reach. However, we believe the data shown in the category represents a broader perception among individuals in an organization and therefore provides an interesting comparison point. Page 2

3 16% 14% 12% 10% 8% 6% 4% 2% 0% Figure 1. Respondents by Role Another surprise: Manufacturing was the most common industry in which respondents worked at 12% (Figure 2). Professional services was second at 11%, just slightly higher than the percentage of respondents who identified themselves as consultants. The top six industries represent nearly twothirds of the respondents. 12% 10% 8% 6% 4% 2% 0% Mining Engineering & Construction Transportation & Logistics Agriculture Wholesale distribution Telecommunications Life sciences Automotive Aerospace & Defense Chemicals Media Pharmaceuticals Oil & gas Higher education Public sector Utilities Retail Healthcare Consumer goods High tech FInance/banking Professional services Manufacturing Figure 2. Respondents by Industry Page 3

4 The functional areas where respondents said they wanted to know more about how to apply analytics and big data technology align with commonly held thoughts on where analytics and big data are important in the enterprise (Figure 3). (Respondents could choose more than one area, so the total is more than 100%.) Exactly half the respondents are looking at finance, while 42% cited sales and marketing. Interest was strong across all functional areas. 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Figure 3. Respondents by Functional Area What They Want to Know We asked respondents to select from a list of 30 subject areas that were important to them, and they could select more than one answer. The overall results are what we expected. Core areas such as data management, report design, and data quality are high, while newer more cutting edge topics such as machine learning are low. And not surprisingly, there is a generally inverse correlation between the topics of interest and those the respondents said they were not familiar with. In other words, the least understood topics tended to be the least important to the respondents. Page 4

5 Business intelligence Data quality Data integration Data management Archiving Report design Data modeling Data warehousing Data governance Data migration Security Search tools Data architecture Predictive analytics Mobile applications Database administration Enterprise content management Data visualization Data profiling User interface design Data supply chain Data as a Service Metadata Software as a Service Data virtualization Social media analytics In-memory computing Location data Semantics and taxonomies Machine learning Percentage Don't Know Percentage Interested Figure 4. Important Topics vs. Topics Not Understood Figures 5 through 34 show how the importance of each topic varies among the different roles of the respondents. In general, respondents in management roles had a higher degree of interest in topics related to big data than respondents in IT roles. In fact, respondents in non-management roles were mainly interested in topics specific to their roles and responsibilities. Page 5

6 Line of Figure 5. Importance of Archiving by Role Line of Figure 6. Importance of Business Intelligence by Role Page 6

7 Line of Figure 7. Importance of Data ure by Role Line of Figure 8. Importance of Data Governance by Role Page 7

8 Line of Figure 9. Importance of Data Integration by Role Line of Figure 10. Importance of Data Migration by Role Page 8

9 Line of Figure 11. Importance of Data Modeling by Role Line of Figure 12. Importance of Data as a Service by Role Page 9

10 Line of Figure 13. Importance of Data Profiling by Role Line of Figure 14. Importance of Data Quality by Role Page 10

11 Line of Figure 15. Importance of Data Management by Role Line of Figure 16. Importance of Data Supply Chain by Role Page 11

12 Line of Figure 17. Importance of Data Virtualization by Role Line of Figure 18. Importance of Data Visualization by Role Page 12

13 Line of Figure 19. Importance of Data Warehousing by Role Line of Figure 20. Importance of Database Administration by Role Page 13

14 Line of Figure 21. Importance of Enterprise Content Management by Role Line of Figure 22. Importance of In-Memory Computing by Role Page 14

15 Line of Figure 23. Importance of Location Data by Role Line of Figure 24. Importance of Machine Learning by Role Page 15

16 Line of Figure 25. Importance of Metadata by Role Line of Figure 26. Importance of Mobile Applications by Role Page 16

17 Line of Figure 27. Importance of Predictive Analytics by Role Line of Figure 28. Importance of Report Design by Role Page 17

18 Line of Figure 29. Importance of Search Tools by Role Line of Figure 30. Importance of Security by Role Page 18

19 Line of Figure 31. Importance of Social Analytics by Role Line of Figure 32. Importance of Software as a Service by Role Page 19

20 Line of Figure 33. Importance of Semantics and Taxonomies by Role Line of Figure 34. Importance of User Interface Design by Role Page 20

21 What They Don t Understand It s a given that almost everyone who has spent time in business or IT management knows core data areas such as security, archiving, data management, or data quality. The survey results reflect that. The survey also shows that there is confusion about key big data terms such as machine learning and inmemory computing among a significant minority of both IT and business managers, as Figures 25 through 64 show. Line of 0.00% 20.00% 40.00% 60.00% 80.00% % Figure 35. Respondents Who Did Not Know Archiving by Role Page 21

22 Line of Figure 36. Respondents Who Did Not Know Business Intelligence by Role Line of Business Process Figure 37. Respondents Who Did Not Know Data ure by Role Page 22

23 Line of Figure 38. Respondents Who Did Not Know Data Governance by Role Line of Figure 39. Respondents Who Did Not Know Data Integration by Role Page 23

24 Line of Figure 40. Respondents Who Did Not Know Data Migration by Role Line of Figure 41. Respondents Who Did Not Know Data Modeling by Role Page 24

25 Line of Figure 42. Respondents Who Did Not Know Data as a Service by Role Line of Figure 43. Respondents Who Did Not Know Data Profiling by Role Page 25

26 Line of 0.00% 20.00% 40.00% 60.00% 80.00% % Figure 44. Respondents Who Did Not Know Data Quality by Role Line of Figure 45. Respondents Who Did Not Know Data Management by Role Page 26

27 Line of Figure 46. Respondents Who Did Not Know Data Supply Chain by Role Line of Figure 47. Respondents Who Did Not Know Data Virtualization by Role Page 27

28 Line of Figure 48. Respondents Who Did Not Know Data Visualization by Role Line of Figure 49. Respondents Who Did Not Know Data Warehousing by Role Page 28

29 Line of Figure 50. Respondents Who Did Not Know Database Administration by Role Line of Figure 51. Respondents Who Did Not Know Enterprise Content Management by Role Page 29

30 Line of Figure 52. Respondents Who Did Not Know In-Memory Computing by Role Line of Figure 53. Respondents Who Did Not Know Location Data by Role Page 30

31 Line of Figure 54. Respondents Who Did Not Know Machine Learning by Role Line of Figure 55. Respondents Who Did Not Know Metadata by Role Page 31

32 Line of Figure 56. Respondents Who Did Not Know Mobile Applications by Role Line of Figure 57. Respondents Who Did Not Know Predictive Analytics by Role Page 32

33 Line of Figure 58. Respondents Who Did Not Know Report Design by Role Line of Figure 59. Respondents Who Did Not Know Search Tools by Role Page 33

34 Line of Figure 60. Respondents Who Did Not Know Security by Role Line of Figure 61. Respondents Who Did Not Know Social Analytics by Role Page 34

35 Line of Figure 62. Respondents Who Did Not Know Software as a Service by Role Line of Figure 63. Respondents Who Did Not Know Semantics and Taxonomies by Role Page 35

36 Line of Figure 64. Respondents Who Did Not Know User Interface Design by Role Managing Data and Data Projects When it comes to topics related to the management of big data and analytics initiatives, the why and how take precedence over measuring and training (Figure 65). Sixty-three percent said strategic planning was most important to them, and the response was higher for executive management (81%) and business managers (75%). People responsible for execution rated strategic planning the lowest. Project management was second at about 60%, led by developers (100%) and IT directors (86%). Change management was consistently important to all roles with two exceptions. No line-of-business owner and 100% of IT directors selected it. Figure 66 shows responses broken out by role. System administrators are the outlier here. They didn t seem interested in any of the management topics, but this is understandable. While their role is vital to the success of any organization, system administrators tend to be at the bottom of the food chain when it comes to planning and executing a big data strategy. Page 36

37 70% 60% 50% 40% 30% 20% 10% 0% Figure 65. Data and Analytics Management Topics Page 37

38 Line of User Training Project Management IT Benchmarking Change Management Strategic Planning Methodologies Corporate Performance Management Figure 66. Management Topics by Role Page 38

39 Big Data and Analytics Plans Fewer than 20% of respondents said their companies had no initiatives related to analytics or big data, less than the 22% who said that big data and analytics are core to their business. More than half, 59%, currently have at least one initiative or will have one within the next 12 months (Figure 67). Companies now have many options to implement the latest analytics technology through the cloud or with minimal impact on existing systems. Yet 63% of those with existing or planned initiatives say they will be deployed internally and integrated with existing systems (Figure 68). Only 4% said their initiative was completely cloud based. Figure 69 shows how big data and analytics initiatives vary for different industries. 35% 30% 25% 20% 15% 10% 5% 0% No plans Big data and analytics are core to our business Will have at least one initiative in the next 12 months Currently have at least one initiative Figure 67. Big Data and Analytics Initiatives Page 39

40 70% 60% 50% 40% 30% 20% 10% 0% Completely cloud based with no direct integration with internal systems or data Internal but offline from out core business systems Cloud based, but with some integration with internal systems and data Internal and integrated with our core business systems and data Figure 68. Nature of Big Data and Analytics Initiatives Page 40

41 Wholesale distribution Utilities Transportation & Logistics Telecommunications Retail Public sector Professional services Pharmaceuticals Oil & gas Mining Media Manufacturing Life sciences High tech Higher education Healthcare FInance/banking Engineering & Construction Consumer goods Chemicals Automotive Agriculture Aerospace & Defense Big data and analytics are core to our business Currently have at least one initiative Will have at least one initiative in the next 12 months No plans 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% Figure 69. Big Data and Analytics Initiatives by Industry Page 41