Cloud Computing and Business Intelligence Market Study

April 6, 2017 Dresner Advisory Services, LLC

2017 Edition Cloud Computing and Business Intelligence Market Study

Wisdom of Crowds® Series

Licensed to Domo 2017 Cloud Computing and Business Intelligence Market Study

Disclaimer:

This report is for informational purposes only. You should make vendor and product selections based on multiple information sources, face-to-face meetings, customer reference checking, product demonstrations, and proof-of-concept applications.

The information contained in this Wisdom of Crowds® Market Study report is a summary of the opinions expressed in the online responses of individuals that chose to respond to our online questionnaire and does not represent a scientific sampling of any kind. Dresner Advisory Services, LLC shall not be liable for the content of this report, the study results, or for any damages incurred or alleged to be incurred by any of the companies included in the report as a result of the report’s content.

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Definitions

Business Intelligence Defined Business intelligence (BI) is “knowledge gained through the access and analysis of business information.”

Business Intelligence tools and technologies include query and reporting, OLAP (online analytical processing), data mining and advanced analytics, end-user tools for ad hoc query and analysis, and dashboards for performance monitoring.

Howard Dresner, The Performance Management Revolution: Business Results Through Insight and Action (John Wiley & Sons, 2007)

Cloud Deployment Models Defined Private Cloud: The cloud infrastructure is provisioned for exclusive use by a single organization comprising multiple consumers (e.g., business units). It may be owned, managed, and operated by the organization, a third party, or some combination of them; and it may exist on or off premises.

Public Cloud: The cloud infrastructure is provisioned for open use by the general public. It may be owned, managed, and operated by a business, academic, or government organization, or some combination of them. It exists on the premises of the cloud provider.

Hybrid Cloud: The cloud infrastructure is a composition of two or more distinct cloud infrastructures (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load balancing between clouds).

Source: National Institute of Standards and Technology

Cloud Business Intelligence Defined Cloud business intelligence is the technologies, tools, and solutions that employ one or more cloud deployment models.

Introduction This year we celebrate the tenth anniversary of Dresner Advisory Services! Our thanks to all of you for your continued support and ongoing encouragement.

Since our founding in 2007, we have worked hard to set the “bar” high—challenging ourselves to innovate and lead the market—offering ever greater value with each successive year.

Our first market report in 2010 set the stage for where we are today. Since that time, we have expanded our agenda and have added new research topics every year. For 2017, we plan to release 15 major reports, including our original BI flagship report—in its eighth year of publication!

This edition of our Cloud Computing and Business Intelligence Market Study is our sixth. We started tracking and analyzing this market dynamic in 2012 when adoption was nascent.

Since that time, deployments of public cloud BI applications have continued to grow steadily with organizations citing substantial benefits over traditional on-premises implementations.

Although there are always challenges to address and improvements to be made, we believe that cloud business intelligence, and especially public cloud offerings, will continue to move into the mainstream.

We hope you enjoy this report!

Best,

Chief Research Officer Dresner Advisory Services

Contents Definitions ...... 3 Business Intelligence Defined ...... 3 Cloud Deployment Models Defined ...... 3 Cloud Business Intelligence Defined ...... 3 Introduction ...... 4 Benefits of the Study ...... 7 Consumer Guide ...... 7 Supplier Tool ...... 7 External Awareness ...... 7 Internal Planning ...... 7 About Howard Dresner and Dresner Advisory Services ...... 8 About Jim Ericson ...... 9 Survey Method and Data Collection ...... 10 Data Quality ...... 10 Executive Summary ...... 12 Study Demographics ...... 13 Geography ...... 14 Functions ...... 15 Vertical Industries ...... 16 Organization Size ...... 17 Analysis and Trends: Business Intelligence Users ...... 19 Perceived Benefits and Barriers for Cloud Business Intelligence...... 19 Importance of Cloud Business Intelligence ...... 21 Current and Future Plans for Cloud Business Intelligence ...... 27 Plans to Use Public Cloud Business Intelligence ...... 33 Plans to Use Cloud BI by Cloud Deployment Model ...... 34 Cloud Business Intelligence Investment ...... 39 Cloud Business Intelligence Feature Requirements ...... 43 Cloud Business Intelligence Architecture ...... 50 Cloud Business Intelligence Security ...... 56

Third-Party Cloud BI Data Connectors ...... 61 Cloud Business Intelligence Licensing ...... 65 Cloud BI Hosting Preferences ...... 69 Cloud BI Provider Preference ...... 74 Industry and Vendor Analysis ...... 76 Cloud Business Intelligence Vendor Ratings ...... 89 Other Dresner Advisory Services Research Reports ...... 90 Appendix: Cloud BI User Survey Instrument ...... 91

Benefits of the Study This DAS Cloud Computing and Business Intelligence Market Study provides a wealth of information and analysis, offering value to both consumers and producers of business intelligence technology and services.

Consumer Guide As an objective source of industry research, consumers use the DAS Cloud Computing and Business Intelligence Market Study to understand how their peers leverage and invest in cloud computing and related BI technologies.

Using our unique vendor performance measurement system, users glean key insights into BI software supplier performance, which enables:

• Comparisons of current vendor performance to industry norms • Identification and selection of new vendors.

Supplier Tool Vendor licensees use the DAS Cloud Computing and Business Intelligence Market Study in several important ways:

External Awareness • Build awareness for business intelligence markets and supplier brands, citing DAS Cloud Computing and Business Intelligence Market Study trends and vendor performance • Gain lead and demand generation for supplier offerings through association with DAS Cloud Computing and Business Intelligence Market Study brand, findings, webinars, etc.

Internal Planning • Refine internal product plans and align with market priorities and realities as identified in the DAS Cloud Computing and Business Intelligence Market Study • Better understand customer priorities, concerns, and issues • Identify competitive pressures and opportunities.

About Howard Dresner and Dresner Advisory Services The DAS End User Data Preparation Market Study was conceived, designed and executed by Dresner Advisory Services, LLC—an independent advisory firm—and Howard Dresner, its President, Founder and Chief Research Officer.

Howard Dresner is one of the foremost thought leaders in business intelligence and performance management, having coined the term “Business Intelligence” in 1989. He has published two books on the subject, The Performance Management Revolution – Business Results through Insight and Action (John Wiley & Sons, Nov. 2007) and Profiles in Performance – Business Intelligence Journeys and the Roadmap for Change (John Wiley & Sons, Nov. 2009). He lectures at forums around the world and is often cited by the business and trade press.

Prior to Dresner Advisory Services, Howard served as chief strategy officer at Hyperion Solutions and was a research fellow at Gartner, where he led its business intelligence research practice for 13 years.

Howard has conducted and directed numerous in-depth primary research studies over the past two decades and is an expert in analyzing these markets.

Through the Wisdom of Crowds® Business Intelligence market research reports, we engage with a global community to redefine how research is created and shared. Other research reports include:

- Wisdom of Crowds “Flagship” Business Intelligence Market study - Advanced and Predictive Analytics - Analytical Data Infrastructure - Big Data Analytics - Collective Insights® - Internet of Things and Business Intelligence - Location Intelligence - Natural Language Analytics

Howard conducts a weekly Twitter “tweetchat” on Fridays at 1:00 p.m. ET. During these live events, the #BIWisdom “tribe” discusses a wide range of business intelligence topics.

You can find more information about Dresner Advisory Services at www.dresneradvisory.com.

About Jim Ericson Jim Ericson is a research director with Dresner Advisory Services.

Jim has served as a consultant and journalist who studies end-user management practices and industry trending in the data and information management fields.

From 2004 to 2013 he was the editorial director at Information Management magazine (formerly DM Review), where he created architectures for user and industry coverage for hundreds of contributors across the breadth of the data and information management industry.

As lead writer, he interviewed and profiled more than 100 CIOs, CTOs, and program directors in a 2010-2012 program called “25 Top Information Managers.” His related feature articles earned ASBPE national bronze and multiple Mid-Atlantic region gold and silver awards for Technical Article and for Case History feature writing.

A panelist, interviewer, blogger, community liaison, conference co-chair, and speaker in the data-management community, he also sponsored and co-hosted a weekly podcast in continuous production for more than five years.

Jim’s earlier background as senior morning news producer at NBC/Mutual Radio Networks and as managing editor of MSNBC’s first Washington, D.C. online news bureau cemented his understanding of fact-finding, topical reporting, and serving broad audiences.

Survey Method and Data Collection As with all of our Wisdom of Crowds® market studies, we constructed a survey instrument to collect data and used social media and crowdsourcing techniques to recruit participants.

Data Quality We carefully scrutinized and verified all respondent entries to ensure that only qualified participants were included in the study.

Executive Summary

Executive Summary - Attitudes toward SaaS and cloud computing have mid-tier importance to respondents that has remained consistent over six years of study (pp. 21-26). Industry sentiment for cloud BI is strong (p. 76). - Thirty-one percent of respondents currently use cloud BI, a 6 percent increase over 2016. More than one-third still have no plans. Successful BI organizations are more likely to use cloud (pp. 27-32). - Actual use and favorable attitudes toward future use of public (multitenant) cloud BI increased in near linear fashion over the last five years (p. 33). - In 2017, public cloud BI use narrowly eclipses private cloud use, though private and hybrid models remain viable and are industry supported. Smaller organizations are more likely to be users (pp. 34-38, pp.77-78). - Forty percent of respondents will increase spending on private cloud; 34 percent will increase budgets for public cloud; and 20 percent will increase hybrid cloud investment. (pp. 39-42). - Ad-hoc query, advanced visualization, dashboards, DI/DQ, end-user self-service, and reporting are the most-required cloud BI features. Big data, ability to write to transactional apps, and CEP gained the most momentum (pp. 43-49). Industry support well accommodates end-user feature requirements (pp. 79-80). - Broad interest in cloud BI architectural features is led by relational database support. RESTful/Web services gained the most momentum (pp. 50-55). Industry support is somewhat aligned with user preferences (pp. 82-83). - For a third year, the most popular response to questions about cloud BI security standard compliance is "don't know" (pp. 56-60). Industry support for cloud BI security grew but remains limited (p. 85). - The top two preferred third-party connectors for cloud BI remain Google Analytics followed by Salesforce.com (pp. 61-64). Industry support is strongest for Salesforce followed by Google Analytics (p. 88). - Trial and buy remains the most popular cloud subscription model and is most popular with marketing/sales respondents (pp. 65-68). Industry support is in line with user preferences (pp. 86-87). - Forty-three percent of respondents have no cloud BI hosting preference; 32 percent prefer BI/analytics vendor hosting; 25 percent prefer third-party cloud providers (pp. 69-73). - AWS is far and away the preferred third-party cloud BI provider, followed by Google Cloud and Microsoft Azure (p. 74).

Study Demographics

Study Demographics Our sixth annual cloud study participants provide a cross-section of data across geographies, functions, organization sizes, and vertical industries. We believe that, unlike other industry research, this supports a more representative sample and better indicator of true market dynamics. We constructed cross-tab analyses using these demographics to identify and illustrate important industry trends.

Geography Survey respondents represent a span of geographies. North America, which includes the United States, Canada, and Puerto Rico, accounts for about half of our survey base. EMEA respondents are the next largest group with 35 percent, followed by Asia Pacific and Latin America (fig. 1).

Geographies Represented

60.0%

50.1% 50.0%

40.0% 34.9%

30.0%

20.0%

9.7% 10.0% 5.3%

0.0% North America Europe, Middle East and Asia Pacific Latin America Africa

Figure 1 – Geographies represented

Functions In 2017, information technology (23 percent) and executive management (20 percent) are the functions most represented in our study (fig. 2). Finance, the BICC, Faculty, and Marketing/Sales are the next most represented. Tabulating results by function enables us to compare and contrast the plans and priorities of different departments within organizations.

Functions Represented 30%

25% 23.2% 20.4% 20%

14.3% 15%

10% 8.9% 7.7% 6.9% 5.6% 5.6% 4.8% 5% 2.6%

Figure 2 – Functions represented

Vertical Industries Our study base includes a cross section of many vertical industries. Technology (14 percent) and Education (11 percent) make up the largest segments, followed by Consulting, Retail/Wholesale, Financial Services, Healthcare, and Manufacturing. We allow and encourage the participation of independent consultants, who often have deeper industry awareness than their customer counterparts. This also yields insight into the partner ecosystem for BI vendors (fig. 3).

Vertical Industries Represented 20%

18%

16% 14% 14% 14%

12% 11% 10%

8% 7% 6% 6% 6% 6% 6% 4% 4% 4% 2% 2% 2% 2% 2% 2% 2% 2% 2% 2% 1% 1% 1% 1% 1%

Figure 3 – Vertical industries represented

Organization Size In 2017, our survey base reflects a balanced mix of small, medium, and large organizations (fig. 4). Small organizations (1-100 employees) account for 30 percent of the sample; mid-sized organizations (101-1,000 employees) account for 27 percent; and the remaining 43 percent is spread across large organizations with more than 1,000 employees. Segmenting respondents by organization size helps us identify differences in behavior, attitudes, and planning often related to headcount.

Organization Sizes Represented 40%

35%

30.0% 30% 27.1%

25% 22.9%

20.0% 20%

15%

10%

0% 1-100 101-1000 1001-5000 More than 5000

Figure 4 – Organization sizes represented

Analysis and Trends

Analysis and Trends: Business Intelligence Users

Perceived Benefits and Barriers for Cloud Business Intelligence The tag cloud breakout of the perceived benefits of cloud BI reflects longstanding attitudes toward cloud computing generally (fig. 5). Cost, maintenance, access, and scalability are the leading perceived benefits. Ease of use and support are other perceived benefits.

Figure 5 – Perceived benefits of cloud business intelligence

Overwhelmingly, the primary barrier to adoption of cloud BI among respondents remains security (fig. 6). As much as in previous years of study, the terms “data” and “security” overtly form the tag cloud, and relative concern about other issues is immaterial by comparison. Traditionally, this reflects enterprise/IT control of information assets as well as compliance issues, though security events continue to demonstrate many proprietary data security failings.

Figure 6 – Perceived barriers to cloud BI adoption

Importance of Cloud Business Intelligence Though cloud computing necessarily overlaps with other BI initiatives, standalone attitudes toward SaaS and cloud computing in 2017 have mid-tier importance to respondents among the 33 topics we currently study (fig. 7). The highest level of interest in 2017 and over time goes to mainstream business intelligence topics including reporting, dashboards, self-service, advanced visualization, and data discovery. With that said, cloud computing continues to rank higher than aggressively marketed topics including big data, social media analysis, and the Internet of Things.

Technologies and Initiatives Strategic to Business Intelligence

Reporting Dashboards Advanced visualization End-user "self-service" Data warehousing Data mining, advanced algorithms, predictive Data discovery Integration with operational processes Mobile device support Data storytelling Enterprise planning / budgeting Governance Embedded BI (contained within an application, portal, etc.) Collaborative support for group-based analysis End-user data preparation and blending Data catalog Search-based interface Software-as-a-Service and cloud computing Big Data (e.g., Hadoop) In-memory analysis Location intelligence / analytics Ability to write to transactional applications Prepackaged vertical / functional analytical applications Streaming data analysis Cognitive BI (e.g., Artificial Intelligence-based BI) Text analytics Open source software Social media analysis (Social BI) Natural language analytics (natural language query/ natural… Complex event processing (CEP) Internet of Things (IoT) Edge computing Video analytics 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Critical Very important Important Somewhat important Not important

Figure 7 – Technologies and initiatives strategic to business intelligence

Across six years of study, the perceived importance of cloud BI remains mostly consistent (fig. 8). Cloud deployments continue to increase over time and, for most organizations, cloud is an important but not burning issue for users. The small peak in 2014 might well reflect a peak of inflated expectations that has settled cloud into the infrastructure mix of topics. Certainly, smaller and younger "straight-to-cloud" organizations might be most interested, familiar, and aware; though we believe by now most organizations are familiar with the opportunities of cloud computing and software as a service.

Cloud BI Importance 2012-2017 100%

90% 3.1 80%

70%

2.6 Not important 60% Somewhat important

50% Important Very important 2.1 40% Critical Mean 30%

20% 1.6

10%

0% 1.1 2012 2013 2014 2015 2016 2017

Figure 8 – Cloud BI importance 2012-2017

Asia Pacific continues to lead other geographical regions as the most enthusiastic proponent of cloud BI in 2017 (fig. 9). This is especially so for the 57 percent who now say cloud BI is "critical" or "very important" (compared to 43 percent in 2016). More than 70 percent of North American respondents and a similar number of EMEA respondents say cloud BI is, at minimum, "somewhat important," perhaps in partial reflection of vendor ubiquity and marketing exposure.

Cloud BI Importance by Geography 100% 5

90% 4.5

80% 4 70%

3.5 60% Critical Very important 50% 3 Important Somewhat important 40% 2.5 Not important 30% Mean 2 20%

1.5 10%

0% 1 Asia Pacific Latin America North America Europe, Middle East and Africa

Figure 9 – Cloud BI importance by geography

The perceived importance of cloud BI is lowest in R&D, IT, and Finance, where traditional enterprise BI provisioning prerogatives still hold the most favor (fig. 10). Conversely, the BICC, Marketing/Sales and Executive Management may well be more likely to appreciate the ability to implement cloud BI quickly and without the need for IT intervention. These same roles are more likely to be aware of function-specific tools and services for BI processes (e.g., Salesforce.com) through third-party providers and cloud-based platforms. As a best-practices provider of expertise and services, the BI Competency Center stands most in favor of cloud.

Cloud BI Importance by Function

100% 4

90% 3.5 80%

70% 3 60% Critical 50% 2.5 Very important 40% Important 2 Somewhat important 30% Not important 20% 1.5 Mean 10%

0% 1 Business Marketing and Executive Finance Information Research and Intelligence Sales Management Technology Development Competency (IT) (R&D) Center

Figure 10 – Cloud BI importance by function

As our cloud BI studies historically find, small organizations (1-100 employee) report the highest interest in cloud BI. Half of respondents consider it "critical" or "very important" (fig. 11). The mean level of "critical" importance thereafter decreases with organization size through mid-sized organizations (101-1,000 employees) and large organizations (>1,000 employees). We see an uptick in overall interest at the largest organizations with 10,000 or more employees, where 70 percent say cloud BI is, at minimum, "somewhat important."

Cloud BI Importance by Organization Size 100%

90%

80%

70%

60% Critical Very important 50% Important 40% Somewhat important Not important 30%

20%

10%

0% 1-100 101-1,000 1,001-2,000 2,001-5,000 5,001-10,000 More than 10,000

Figure 11 – Cloud BI importance by organization size

In our 2017 sample, Financial Services reports the highest weighted mean interest in cloud BI and the most "critical" and "very important" responses (fig. 12). Education, Business Services, and Retail/Wholesale are the next most interested in cloud BI. Industries that trail mean levels of interest in 2017 include Food/Beverage/Tobacco, Manufacturing, Telecommunications, and Healthcare.

Importance of Cloud BI by Selected Vertical Industry 100% 4 90% 3.5 80% 70% 3 60%

50% 2.5 Critical 40% Very important 2 30% Important 20% Somewhat important 1.5 10% Not important 0% 1 Mean

Figure 12 – Importance of cloud BI by selected vertical industry

Current and Future Plans for Cloud Business Intelligence Fig 13 shows year-over-year changes in the use of and plans for cloud BI (without regard for public, private, or hybrid cloud BI models) (fig. 13). As we would expect, cloud use is increasing over time, a trend that should continue as companies retire older infrastructure. In 2017, 31 percent of respondents say they currently use cloud BI / analytics, a 6 percent increase from 2016. The number evaluating is mostly steady while the number of those considering the use of cloud BI/analytics fell 5 percent to offset the increase in current users. In both 2016 and 2017, more than one-third of respondents say they still have no plans to use cloud BI / analytics.

Plans to Use Cloud BI 2016-2017 40%

35%

30%

25%

20%

15%

10%

0% Yes. We use cloud-based We are currently We may use cloud-based No. We have no plans to BI / Analytics today evaluating cloud-based BI BI / Analytics in the use cloud-based BI / / Analytics software future Analytics at all.

2016 2017

Figure 13 – Plans to use cloud BI 2016-2017

By region, Asia-Pacific respondents are most likely to currently use or be in the evaluation process for cloud BI (fig. 14). To a lesser degree, North American and Latin American respondents are about equally likely to currently use cloud BI. EMEA respondents trail all other regions in current use, evaluation, and are most likely (40 percent) to have no plans at all.

Plans to Use Cloud BI by Geography 100%

90%

80%

70% Yes. We use cloud-based BI / 60% Analytics today We are currently evaluating cloud- 50% based BI / Analytics software We may use cloud-based BI / 40% Analytics in the future

30% No. We have no plans to use cloud-based BI / Analytics at all 20%

10%

0% Latin America Europe, Middle Asia Pacific North America East and Africa

Figure 14 – Plans to use cloud BI by geography

Favorable sentiment for cloud BI falls most strongly to deadline and achievement- oriented roles in Executive Management and Marketing/Sales (fig. 15). Fifty-seven percent of executive respondents are current users, as are 50 percent in Marketing/Sales and the BICC. Back-office IT and Finance respondents are least likely to currently use or evaluate cloud BI.

Plans to Use Cloud BI by Function 100%

90%

80% Yes. We use cloud-based 70% BI / Analytics today

60% We are currently 50% evaluating cloud-based BI / Analytics software

40% We may use cloud-based BI / Analytics in the future 30%

20% No. We have no plans to use cloud-based BI / Analytics at all 10%

0% Executive Marketing Business Research and Information Finance Management and Sales Intelligence Development Technology Competency (R&D) (IT) Center

Figure 15 – Plans to use cloud BI by function

Small organizations with one to 100 employees are most likely (44 percent) to currently use cloud BI (fig. 16). Usage declines at mid-sized (31percent) and some large organizations (1,001-5,000 employees) (24 percent) before rebounding to 32 percent at very large organizations (> 5,000 employee). Organizations with 1,001-5,000 employees are most likely (49 percent) to have no plans to use cloud BI/analytics.

Plans to Use Cloud BI by Organization Size 100%

90%

80% Yes. We use cloud-based 70% BI / Analytics today

60% We are currently evaluating cloud-based BI 50% / Analytics software We may use cloud-based 40% BI / Analytics in the future

30% No. We have no plans to use cloud-based BI / 20% Analytics at all

10%

0% 1-100 101-1000 1001-5000 More than 5000

Figure 16 – Plans to use cloud BI by organization size

Current use and future planning for cloud BI/analytics skews unevenly by industry. Business Services is most likely (56 percent) to currently use cloud BI/analytics, followed somewhat distantly (39 percent) by users in Financial Services (fig. 17). Future plans are nonetheless strongest in Financial Services. Retail/Wholesale and Healthcare respondents are 33 percent or more likely to currently use cloud BI/analytics. Manufacturing, Telecommunications, and Higher Education are the industries least likely to currently use cloud BI/analytics.

Plans to Use Cloud BI by Selected Vertical Industry 100%

90%

80% Yes. We use cloud-based 70% BI / Analytics today

60% We are currently evaluating cloud-based BI 50% / Analytics software 40% We may use cloud-based BI / Analytics in the future 30%

20% No. We have no plans to use cloud-based BI / 10% Analytics at all 0%

Figure 17 – Plans to use cloud BI by vertical industry

Success with business intelligence correlates with current use to cloud BI. Organizations that consider themselves as “completely successful" are 40 percent likely to be current users, and those that are “somewhat successful” are 38 percent likely to be users (fig. 18). Conversely, organizations that consider themselves somewhat unsuccessful at business intelligence are just 23 percent likely to currently use cloud BI, and less than 10 percent of completely unsuccessful organizations are current users. This raises the question of causation/correlation. But unsuccessful organizations say they are or may be open to cloud BI analytics use in the future.

Plans to Use Cloud BI by BI Success

100%

90%

80% Yes. We use cloud-based 70% BI / Analytics today

60% We are currently evaluating cloud-based BI / Analytics software 50% We may use cloud-based BI / Analytics in the future 40%

30% No. We have no plans to use cloud-based BI / Analytics at all 20%

10%

0% Completely agree Agree somewhat Disagree somewhat Disagree

Figure 18 – Plans to use cloud BI by success with BI

Plans to Use Public Cloud Business Intelligence Across five years of data, actual use and favorable attitudes toward future use of public (multitenant) cloud BI increased in near linear fashion (fig. 19). In 2017, one-third of all respondents currently use public cloud (compared to 13 percent in our inaugural 2012 study). However, year-over-year, 12-month, and 24-month plans decreased slightly (as they also did in 2016), perhaps indicating a near-term plateau. We believe generic definitions of public cloud BI are by now well understood to imply single instance, off- premises, multitenant services. While a majority of respondents still resist public cloud, we expect Marketing/Sales, Executive Management, and other underserved functions with relatively urgent goals and time frames will remain first movers to public cloud BI use.

Plans for Public Cloud BI 2012-2017 100%

90%

80% 53% 51% 70% 57% 68% 73% 71% 60% No plans

50% Next year This year 9% 7% 40% 10% 6% Today 9% 30% 6% 9% 6% 8% 6% 20% 6% 33% 7% 29% 24% 10% 17% 20% 13% 0% 2012 2013 2014 2015 2016 2017

Figure 19 – Plans for public cloud BI 2012-2017

Plans to Use Cloud BI by Cloud Deployment Model In 2017, public cloud BI use narrowly eclipses private cloud use (fig. 20). We find this finding to be notable and somewhat surprising since it has been common in other technology investments to bring hosted models in house, rather than the reverse. Also, we expected hybrid models might grow in relation to other models, but this has plainly not happened. One conclusion could be that organizations developed a familiarity and comfort level with public cloud BI over time that led to greater service-based adoption. (Also see licensing models, fig.51, p. 65.)

Plans for Cloud BI by Deployment Model

Private cloud BI

Hybrid cloud BI

Public cloud BI

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Discontinued No plans Plan to use next year Plan to use this year Using today

Figure 20 – Plans for cloud BI by deployment model

As we found in earlier studies, private and public cloud BI models are about equally favorable among respondents in North America (fig 21). Future deployment plans in North America are at 15 percent or less, and lowest for hybrid models. Sentiment for public cloud is second highest in Asia Pacific, which also reports a nearly 20 percent increase in private cloud use next year. Excluding Latin America, where public and hybrid cloud BI use is nil, EMEA reports the lowest current use of all models.

Plans for Cloud BI by Deployment Model and Geography 100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0% Public Hybrid Private Public Hybrid Private Public Hybrid Private Public Hybrid Private cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI North America Asia Pacific Europe, Middle East and Latin America Africa

Discontinued No plans Plan to use next year Plan to use this year Using today

Figure 21 – Plans for cloud BI by deployment model and geography

By function, Executive Management is the strongest advocate of all cloud BI models (fig. 22). Marketing/Sales takes the opposite view and is more likely to use or plan for public cloud BI in the future. Somewhat surprisingly, Marketing/Sales report the lowest current use of public cloud BI outside of R&D. We are not surprised to see IT and Finance hesitant to embrace cloud BI models (especially public ones), though the BICC is strongly exploring public and private cloud BI models as a deliverable for their organization.

Plans for Cloud BI by Deployment Model and Function 100% 90% 80% 70% 60% 50% 40% 30% 20% 10%

Public cloud BI cloud Public BI cloud Public Public cloud BI cloud Public BI cloud Public BI cloud Public BI cloud Public

Hybrid cloud BI cloud Hybrid BI cloud Hybrid BI cloud Hybrid Hybrid cloud BI cloud Hybrid BI cloud Hybrid BI cloud Hybrid

Private cloud BI cloud Private BI cloud Private Private cloud BI cloud Private BI cloud Private BI cloud Private BI cloud Private Executive Marketing and Information Finance Business Research and Management Sales Technology (IT) Intelligence Development Competency (R&D) Center Discontinued No plans Plan to use next year Plan to use this year Using today

Figure 22 – Plans for cloud BI by deployment model and function

Small organizations with 1-100 employees are most likely to use public (45 percent) over private (27 percent) cloud BI models (fig. 23). Conversely, very large organizations with 5,000 or more employees (and the most legacy IT investment) clearly prefer private cloud BI (52 percent) over public (22 percent). Very large organizations are also the only segment that prefers hybrid over public cloud BI models, which may reflect pressure to augment on-premises systems with hosted applications and data. Generally, favorability for private versus public cloud BI models begins with mid-sized organizations (101-1,000 employees) and extends to larger peers.

Plans for Cloud BI by Deployment Model and Organization Size 100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

Discontinued No plans Plan to use next year Plan to use this year Using today

Figure 23 – Plans for cloud BI by deployment model and organization size

In 2017, technology industry respondents are most likely to use public cloud BI and are also strong private cloud users (fig. 24). Somewhat surprisingly, Healthcare respondents in 2017 also report strong private (50 percent) as well as public cloud BI use (50 percent). Retail/Wholesale respondents also report 50 percent private cloud usage but are much less likely to use public cloud. Financial Services respondents are strong users of private cloud but very unlikely public cloud users. Higher Education trails all industries in cloud BI use.

Plans for Cloud BI by Deployment Model and Industry 100% 90% 80% 70% 60% 50% 40% 30% 20% 10%

Public cloud BI cloud Public Public cloud BI cloud Public BI cloud Public BI cloud Public BI cloud Public

Hybrid cloud BI cloud Hybrid BI cloud Hybrid Hybrid cloud BI cloud Hybrid BI cloud Hybrid BI cloud Hybrid

Private cloud BIcloud Private Private cloud cloud BI Private cloud BI Private cloud BI Private cloud BI Private Technology Education (Higher Financial Services Retail and Healthcare Ed) Wholesale

Discontinued No plans Plan to use next year Plan to use this year Using today

Figure 24 – Plans for cloud BI by deployment model and industry

Cloud Business Intelligence Investment We asked our study base whether they will increase, maintain, or decrease investment across the public, private, and hybrid cloud BI models in 2017 (fig. 25). Respondents tell us they are increasing spending across all three models: 40 percent will increase private cloud spending, 34 percent will increase budgets for public cloud, and 20 percent will increase hybrid cloud investment. Stable budgets are highest for hybrid cloud. Decrease/discontinue rates are in the range of 20 percent (and may in part reflect shifting cloud investment priorities).

Cloud BI Investment 100%

90%

80% Increase 70% Maintain

60% Decrease Discontinue 50%

40%

30%

20%

10%

0% Public cloud BI Hybrid cloud BI Private cloud BI

Figure 25 – Cloud BI investment

By region, EMEA respondents (traditionally a conservative market) are most likely (> 60 percent) to increase investment in private versus public (31 percent) cloud BI (fig. 27). In contrast, Asia-Pacific respondents are most likely to boost investment (43 percent) in public versus private (17 percent) cloud BI. North American respondents are less likely investors overall but plan greater increases in private (39 percent) versus public (31 percent) or hybrid (15 percent) cloud BI.

Cloud BI Investment by Geography 100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0% Public Hybrid Private Public Hybrid Private Public Hybrid Private cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI North America Europe, Middle East and Africa Asia Pacific

Discontinue Decrease Maintain Increase

Figure 26 – Cloud BI investment by geography

With strong support in the BICC, respondents in Executive Management (who are likely to seek innovative or cost-effective solutions) are most likely to support increases in public cloud BI (fig. 26). Notably, BICC respondents are, by far, the most likely to decrease or discontinue investment in private and hybrid cloud BI. We note that Marketing/Sales support for public cloud trails both Executive Management and BICC. Not surprisingly, IT is most likely to report increases (50 percent) in private cloud BI and is the weakest proponent for increased investment in public cloud BI.

Cloud BI Investment by Function

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0% Public Hybrid Private Public Hybrid Private Public Hybrid Private Public Hybrid Private cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI cloud BI Executive Management Marketing and Sales Information Technology (IT) Business Intelligence Competency Center

Discontinue Decrease Maintain Increase

Figure 27 – Cloud BI investment by function

Increased investment in cloud BI models varies somewhat unevenly by organization size (fig. 28). In 2017, mid-sized (101-1,000 employees) and larger organizations are 50 percent or more likely to increase private cloud BI investments. Small organizations (1-100 employees), already more likely invested in cloud BI (fig. 23, p. 37) are less likely to increase public and private cloud BI holdings in 2017.

Cloud BI Investment by Organization Size 100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

Discontinue Decrease Maintain Increase

Figure 28 – Cloud BI investment by organization size

Cloud Business Intelligence Feature Requirements Respondents show interest in a wide range of cloud BI features. In 2017, conventional BI functionality, led by ad-hoc query, advanced visualization, dashboards, DI/DQ, end- user self-service, and reporting lead the list of the most-required cloud BI features (fig. 29). These top features are, at minimum, somewhat important to well more than 90 percent of respondents. Data mining, data discovery, search interface, and end-user data blending are respondents’ next most important features. Overall, we believe cloud BI feature requirements closely mirror traditional BI preferences.

Cloud BI Feature Requirements 0% 20% 40% 60% 80% 100% Ad-hoc query Advanced visualization Personalized dashboards Data integration / data quality… End-user "self-service" Production reporting Data mining and advanced… Data discovery Search interface End-user data blending or… Data catalog Location intelligence/analytics Collaborative support for group-… Big data (e.g., Hadoop) support Prepackaged vertical/functional… In-memory support Ability to write to transactional… Natural language analytics Complex event processing (CEP) Text analytics Social media analysis (Social BI)

Critical Very important Important Somewhat important Unimportant

Figure 29 – Cloud BI feature requirements

Across our last five years of data, interest in most cloud BI features has stayed in a mostly unchanged ranking of importance (fig. 30). The importance of several features is steady or increased in 2017, including the top features: ad-hoc query, dashboards, visualization, DI/DQ, and production reporting. In contrast, end-user self-service lost some momentum compared to earlier studies. Some lower feature priorities gain some prominence in 2017, notably big data, ability to write to transactional apps, and complex event processing.

Cloud BI Feature Priorities 2013-2017 4.5 4.5 4 4 3.5 3.5 3 3 2.5 2.5 2 2 1.5 1.5 1 1 0.5 0.5 0 0

2013 2014 2015 2016 2017 Mean

Figure 30 – Cloud BI feature priorities 2013-2017

Figure 31 provides another informative view in changing cloud BI feature priorities year over year. As noted in fig 30 (p. 45), big data, ability to write to transactional apps, and CEP gained momentum. The biggest year-over-year declines are in data discovery and in-memory support.

Change in Cloud BI Feature Priorities 2016-2017

Big data (e.g., Hadoop) support Ability to write to transactional applications Complex event processing (CEP) Production reporting Data mining and advanced algorithms Text analytics Ad-hoc query End-user self-service Advanced visualization Data integration/data quality tools/ETL Collaborative support for group-based analysis Location intelligence/analytics Search Interface Personalized dashboards Social media analysis (SocialBI) End-user data blending or "mashups" Pre-packaged vertical/functional analytical… In-memory support Data discovery -6% -4% -2% 0% 2% 4% 6% 8% 10%

Figure 31 – Change in cloud BI feature priorities 2016-2017

Cloud BI feature requirements vary unevenly by geography (fig. 32). North American respondents show the highest interest in ad-hoc query and end-user self-service. Asia- Pacific respondents lead interest in advanced visualization. Latin American respondents are most interested in personalized dashboards. EMEA respondents trail interest in almost all feature requirements.

Cloud BI Feature Requirements by Geography

Ad-hoc query Social media analysis (Social BI) 5 Advanced visualization Text analytics 4.5 Personalized dashboards 4 Data integration / data quality Complex event processing (CEP) 3.5 tools/ETL 3 Natural language analytics 2.5 End-user "self-service" 2 Ability to write to transactional 1.5 Production reporting applications 1

Data mining and advanced In-memory support algorithms

Prepackaged vertical/functional Data discovery analytical applications

Big data (e.g., Hadoop) support Search interface Collaborative support for group- End-user data blending or based analysis "mashups" Location intelligence/analytics Data catalog

North America Asia Pacific Europe, Middle East and Africa Latin America

Figure 32 – Cloud BI feature requirements by geography

By function, the BICC leads most categories of feature interest including ad-hoc query, advanced visualization, DI/DQ, and many more (fig. 32). This likely reflects the breadth of responsibilities and undertakings and the BICC's role as proxy R&D BI arm for the organization. Marketing/Sales is most likely to require advanced visualization. Finance trails interest in most feature categories, and IT and R&D are not pursuing most cloud BI feature requirements.

Cloud BI Feature Requirements by Function Ad-hoc query Social media analysis (Social Advanced visualization BI) 5 Text analytics 4.5 Personalized dashboards 4 Complex event processing Data integration / data quality (CEP) 3.5 tools/ETL 3 Natural language analytics 2.5 End-user "self-service" 2 Ability to write to transactional 1.5 Production reporting applications 1

Data mining and advanced In-memory support algorithms

Prepackaged Data discovery vertical/functional analytical…

Big data (e.g., Hadoop) support Search interface

Collaborative support for End-user data blending or group-based analysis "mashups" Location intelligence/analytics Data catalog

Executive Management Marketing and Sales Information Technology (IT) Finance Business Intelligence Competency Center Research and Development (R&D)

Figure 33 – Cloud BI feature requirements by function

Organizations of different sizes are most similar in their appreciation for the top cloud BI feature requirements, ad-hoc query, advanced visualization, dashboards and DI/DQ, but are more skewed in other areas (fig. 34). Very large (> 5,000) organizations show strong interest in top requirements and in 2017, lead interest in all lesser features. Small organizations narrowly lead interest in dashboards, while organizations with 1,001- 5,000 employees have the most interest in advanced visualization and DI/DQ.

Cloud BI Feature Requirements by Organization Size

Data mining and advanced In-memory support algorithms

Prepackaged vertical/functional Data discovery analytical applications

Big data (e.g., Hadoop) support Search interface Collaborative support for group- End-user data blending or based analysis "mashups" Location intelligence/analytics Data catalog

1-100 101-1000 1001-5000 More than 5000

Figure 34 – Cloud BI feature requirements by organization size

In 2017, cloud BI feature requirements vary noticeably by industry (fig. 35). With the exception of Healthcare, interest in ad-hoc query is tightly grouped across industries. Business Services reports standout interest in advanced visualization but trails mean interest in several other feature categories. Financial Services interest is strongest in dashboards and end-user data blending. Higher Education reports the most interest in DI/DQ, production reporting, data mining, and data catalog. Retail/Wholesale shows near-mean or lower interest in most features.

Cloud BI Feature Requirements by Industry

Data mining and advanced In-memory support algorithms

Prepackaged vertical/functional Data discovery analytical applications

Big data (e.g., Hadoop) support Search interface Collaborative support for group- End-user data blending or based analysis "mashups" Location intelligence/analytics Data catalog

Financial Services Education (Higher Ed) Healthcare Retail and Wholesale Business Services

Figure 35 – Cloud BI feature requirements by industry

Cloud Business Intelligence Architecture Architectural requirements for cloud BI are spread across several features of interest (fig. 36). The most important architectural feature for cloud BI in 2017 (as in 2016) is relational database support, which is either "critical" or "very important" to 71 percent of respondents. Automatic upgrades, open client connectors, and connectors to on- premises apps are next most important. The breadth of architectural requirements is notable with every category, except virtualization, at or above 50 percent "critical" or "very important."

Cloud BI Architectural Requirements 0% 20% 40% 60% 80% 100%

Relational database support

Automatic upgrades Open client connector (e.g., ODBC, JDBC) Connectors to on-premises applications and data (e.g., ERP,… RESTful/Web Services API Multi-dimensional database support Real-time query to third-party cloud applications, cloud data… Cloud database connectors (e.g., database.com, Redshift,… Data virtualization Cloud application connections (e.g., Salesforce, NetSuite) Multi-tenancy (single executable supporting multiple customers)

Critical Very important Important Somewhat important Unimportant

Figure 36 – Cloud BI architectural requirements

An informative view of year-over-year changes in sentiment toward cloud architectures is shown in fig. 37. Though it ranks as the fifth priority overall in 2017, interest in RESTful/Web services API gained more than 3 percent in 2017. Interest in automatic upgrades also improved and moved up a place in overall rankings compared to 2016. The least "critical" feature in 2017, data virtualization, also lost the most interest year over year. Interest in cloud application connectors and multidimensional database support also declined year over year.

Changes in Cloud BI Architecture Priority 2016-2017

RESTful/Web Services API

Automatic upgrades Cloud database connectors (e.g., Amazon Redshift, database.com, SimpleDB, CloudSQL) Relational database support Connectors to on-premises applications and data (e.g., ERP, CRM) Open client connector (e.g., ODBC, JDBC) Real-time query to third-party cloud applications, cloud data sources and on-premise systems Multi-tenancy (single executable supporting multiple customers) Multi-dimensional database support Cloud application connections (e.g., Salesforce, Netsuite, Taleo) Data virtualization

-6% -5% -4% -3% -2% -1% 0% 1% 2% 3% 4%

Figure 37 – Changes in cloud BI architecture priority 2016-2017

Interest in cloud BI architectural requirements varies by geography (fig. 38). North American respondents report the most or second-most interest in architecture features in all but one category. Asia-Pacific respondents’ interest is most pronounced in relational database support, open client connectors, cloud database connectors, and cloud application connectors, reaffirming the region's cloud investment leadership (fig. 26, p. 40). EMEA and Latin America respondents report the lowest levels of interest in all architectural features sampled.

Cloud BI Architectural Requirements by Geography Relational database support Multi-tenancy (single 5 executable supporting 4.5 Automatic upgrades multiple customers) 4 3.5

Cloud application connections 3 Open client connector (e.g., (e.g., Salesforce, NetSuite) 2.5 ODBC, JDBC) 2 1.5 1 Connectors to on-premises Data virtualization applications and data (e.g., ERP, CRM)

Cloud database connectors (e.g., database.com, Redshift, RESTful/Web Services API SimpleDB, CloudSQL) Real-time query to third-party cloud applications, cloud data Multi-dimensional database sources, and on-premises support systems North America Asia Pacific Europe, Middle East and Africa Latin America

Figure 38 – Cloud BI architectural requirements by geography

Interest in cloud BI architectural requirements varies rather broadly by function (fig. 39). BICC respondents have the broadest range of interest and lead categories (especially those that are cloud related), including open client connectors, RESTful/Web services, real-time query to third-party cloud, cloud database connectors, cloud app connections, and multi-tenancy. Research and Development reports the highest interest in more conventional relational database support, connection to on-premises applications/data and multidimensional database support. Executive Management has the most interest in automatic upgrades.

Cloud BI Architectural Requirements by Function Relational database support Multi-tenancy (single 5 executable supporting multiple 4.5 Automatic upgrades customers) 4 3.5

Cloud application connections 3 Open client connector (e.g., (e.g., Salesforce, NetSuite) 2.5 ODBC, JDBC) 2 1.5 1 Connectors to on-premises Data virtualization applications and data (e.g., ERP, CRM)

Cloud database connectors (e.g., database.com, Redshift, RESTful/Web Services API SimpleDB, CloudSQL) Real-time query to third-party cloud applications, cloud data Multi-dimensional database sources, and on-premises support systems Executive Management Marketing and Sales Information Technology (IT) Finance Business Intelligence Competency Center Research and Development (R&D)

Figure 39 – Cloud BI architectural requirements by function

Organizations of different sizes vary somewhat in their architectural requirements for cloud BI features (fig. 40). Large organizations of 1,001-5,000 employees lead interest in multiple categories including automatic upgrades, connectors to on-premises apps, multidimensional database support, and data virtualization. Very large organizations (> 5,000 employees) also have high interest in relational database, open client connectors, and lead real-time query interest. Small organizations (1-100 employees) are most interested in RESTful/Web services but least interested in several other features, notably relational database support, open client connectors, and connections to on- premises apps. Mid-sized organizations (101-1,000 employees) lead interest only in the area of cloud application (e.g., Salesforce, NetSuite) connections.

Cloud BI Architectural Requirements by Organization Size Relational database support Multi-tenancy (single 5 executable supporting multiple 4.5 Automatic upgrades customers) 4 3.5

Cloud application connections 3 Open client connector (e.g., (e.g., Salesforce, NetSuite) 2.5 ODBC, JDBC) 2 1.5 1 Connectors to on-premises Data virtualization applications and data (e.g., ERP, CRM)

1-100 101-1000 1001-5000 More than 5000

Figure 40 – Cloud BI architectural requirements by organization size

Preferences for cloud BI architectural requirements vary somewhat by industry (fig. 41). Retail/Wholesale is most likely to require relational database support, open client connectors, connection to on-premises apps, RESTful/Web services, and cloud app connections. Financial Services is most interested in automatic upgrades, cloud database connections, and multi-tenancy. Healthcare's greatest interest is in open client connectors and lowest interest is in RESTful/Web services API. Business Services and Higher Education report below-average interest in most architectural requirements.

Cloud BI Architectural Requirements by Industry

Relational database support Multi-tenancy (single 5 executable supporting multiple 4.5 Automatic upgrades customers) 4 3.5

Cloud application connections 3 Open client connector (e.g., (e.g., Salesforce, NetSuite) 2.5 ODBC, JDBC) 2 1.5 1 Connectors to on-premises Data virtualization applications and data (e.g., ERP, CRM)

Financial Services Retail and Wholesale Healthcare Education (Higher Ed) Business Services

Figure 41 – Cloud BI architectural requirements by industry

Cloud Business Intelligence Security We asked respondents to identify cloud BI security requirements in 2017 and, for a third year, the most popular response is "don't know" (fig. 42). This finding likely represents a gap between general awareness and those in positions of responsibility. Among standards, ISO 27001 remains the most required security standard across all six years of our study. HIPAA, SAS 70 AICPA, and PCI/DSS are the standards next most cited as requirements.

Cloud BI Security Requirements

Don't know

ISO 27001 (Specification for Information Security Management System) HIPAA (Health Insurance Portability and Accountability Act)

SAS 70 AICPA Auditing Standard (now SSAE 16)

PCI DSS (Payment Card Industry Data Security Standard)

SOC 2 TYPE 2

None

FISMA (Federal Information Security Management Act )

FERPA (Family Educational Rights and Privacy Act)

FIPS 140-2 (Federal Information Processing Standard)

TRUSTe

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Figure 42 – Cloud BI security requirements

The lack of cloud BI security awareness is a phenomenon that varies by region (fig. 43). Notably, EMEA respondents followed by Latin America are, by far, the most likely to not identify specific security awareness. In contrast, large majorities of North American and Asia-Pacific respondents have at least some awareness of security requirements. Asia- Pacific respondents are by far most likely to report instances of ISO 27001 in their organization and report more HIPAA awareness than North American counterparts. We might also expect cloud BI deployments by region to correlate with security awareness. North America (SAS 70, PCI/DSS, FISMA) and Asia Pacific (SOC 2) perform better than average in this regard, especially toward regional security standards.

Cloud BI Security Requirements by Geography

Don't know 70% ISO 27001 (Specification for TRUSTe 60% Information Security Management System) 50% 40% HIPAA (Health Insurance FIPS 140-2 (Federal Information Portability and Accountability Processing Standard) 30% Act) 20% 10% 0% FERPA (Family Educational SAS 70 AICPA Auditing Rights and Privacy Act) Standard (now SSAE 16)

FISMA (Federal Information PCI DSS (Payment Card Industry Security Management Act ) Data Security Standard)

None SOC 2 TYPE 2

North America Asia Pacific Europe, Middle East and Africa Latin America

Figure 43 – Cloud BI security requirements by geography

Across functions, there is not a great deal of awareness of cloud BI security standards, even among IT respondents (fig. 44). Alarmingly, those who "don't know" are most likely in Finance and Executive Management. At the same time, Finance respondents are most aware of 27001, HIPAA, and SAS 70 AICPA. By contrast, respondents in the BICC (which is a center of best practices as well) are most likely to have some awareness across multiple standards (ISO 27001, PCI/DSS, SOC 2, and lesser requirements). The notable absence of IT awareness ranging from "none" to "don't know" begs the question of who is "minding the store," since technology controls directly manage security (if not policy and liability) issues related to a breach.

Cloud BI Security Requirements by Function

Don't know 50% ISO 27001 (Specification for TRUSTe Information Security 40% Management System)

30% HIPAA (Health Insurance FIPS 140-2 (Federal Information Portability and Accountability Processing Standard) 20% Act) 10%

0% FERPA (Family Educational SAS 70 AICPA Auditing Standard Rights and Privacy Act) (now SSAE 16)

FISMA (Federal Information PCI DSS (Payment Card Industry Security Management Act ) Data Security Standard)

None SOC 2 TYPE 2

Executive Management Information Technology (IT) Finance Business Intelligence Competency Center Research and Development (R&D)

Figure 44 – Cloud BI security requirements by function

Not surprisingly, large and very large organizations with codified IT and data governance organizations, policies, and controls generally have much higher awareness of cloud BI security requirements than smaller peers with less-formal processes (fig. 45). Indeed, small organizations (1-100 employees) have below-average awareness of nearly all cloud BI security requirements, and mid-sized organizations (101-1,000 employees) are only somewhat more aware.

Cloud BI Security Requirements by Organization Size Don't know 80% ISO 27001 (Specification for TRUSTe 70% Information Security Management System) 60% 50% HIPAA (Health Insurance FIPS 140-2 (Federal Information 40% Portability and Accountability Processing Standard) 30% Act) 20% 10% 0% FERPA (Family Educational SAS 70 AICPA Auditing Standard Rights and Privacy Act) (now SSAE 16)

FISMA (Federal Information PCI DSS (Payment Card Industry Security Management Act ) Data Security Standard)

None SOC 2 TYPE 2

1-100 101-1000 1001-5000 More than 5000

Figure 45 – Cloud BI security requirements by organization size

Cloud BI security requirement awareness also varies by industry (fig. 46). Business Services and Higher Education respondents are most likely to report "don't know" while Retail/Wholesale respondents appear to be most aware. Technology respondents are most likely to require ISO 27001 and HIPAA standards, while Financial Services predictably lists SAS 70 as the top cloud BI security requirement. Higher Education respondents are most likely to require FERPA, FISMA, and FIPS 140-2.

Cloud BI Security Requirements by Industry

Don't know 90% ISO 27001 (Specification for TRUSTe 80% Information Security 70% Management System) 60% FIPS 140-2 (Federal 50% HIPAA (Health Insurance Information Processing 40% Portability and Standard) 30% Accountability Act) 20% 10% 0% FERPA (Family Educational SAS 70 AICPA Auditing Rights and Privacy Act) Standard (now SSAE 16)

PCI DSS (Payment Card FISMA (Federal Information Industry Data Security Security Management Act ) Standard)

None SOC 2 TYPE 2

Financial Services Education (Higher Ed) Business Services Healthcare Technology Retail and Wholesale

Figure 46 – Cloud BI security requirements by industry

Third-Party Cloud BI Data Connectors Beginning in 2015, we asked respondents to specify preferred third-party connectors for cloud BI. Since then, the top two choices remain Google Analytics followed by Salesforce.com (fig. 47). In 2017, Dropbox falls to fifth place, surpassed by Google Drive and Facebook. Twitter also falls behind LinkedIn and SurveyMonkey. We believe these connectors (though plainly not in universal demand) reflect both the popularity of off-premises data platforms and the value of data within. They also reflect demand for cloud BI integration with a variety of Web-based sources versus conventional practices addressing in-house resources.

Cloud BI Third-Party Data Connectors 70%

60%

50%

40%

30%

20%

10%

Figure 47 – Cloud BI third-party data connectors

2017 interest in the most popular cloud BI connector, Google Analytics, is by far highest in Asia Pacific and is lowest in EMEA (fig. 48). Salesforce interest is expectedly strongest in North America and not distantly followed in interest by Latin America. Facebook interest is strongest in Latin America. Asia Pacific leads interest in SurveyMonkey, Azure SQL, Google+ and YouTube. EMEA interest in third-party data connectors almost universally trails other regions.

Third-Party Data Connectors for Cloud BI by Geography

Google Analytics VKontakte100% Salesforce radian6 Google Drive 90% Freshbooks 80% Facebook 70% New Relic Dropbox 60% 50% Majestic SEO LinkedIn 40% 30% Searchmetrics SurveyMonkey 20% 10% Optimizely 0% Twitter

Webtrends Windows Azure SQL

Foursqaure Google AdWords

Pingdom Google+

Eloqua YouTube

HubSpot MailChimp Zendesk Instagram Marketo North America Asia Pacific Europe, Middle East and Africa Latin America

Figure 48 – Third-party data connectors for cloud BI by geography

Third-party connectors to social media sites tend to resonate strongly with Marketing/Sales respondents and, in 2017, this is again the case for Google Analytics, Facebook, LinkedIn, SurveyMonkey, and Twitter among others (fig. 49). Most surprising is that this year's sample reports the greatest support for Salesforce in Finance, a result we cannot immediately explain. We also note that IT and BICC generally pay low attention to third-party data connectors, indicating in part that these are mostly simple and straightforward end-user exercises.

Third-Party Data Connectors for Cloud BI by Function Google Analytics VKontakte110% Salesforce radian6 100% Google Drive Freshbooks 90% Facebook 80% New Relic 70% Dropbox 60% Majestic SEO 50% LinkedIn 40% 30% Searchmetrics SurveyMonkey 20% 10% Optimizely 0% Twitter

Webtrends Windows Azure SQL

Foursqaure Google AdWords

Pingdom Google+

Eloqua YouTube

HubSpot MailChimp Zendesk Instagram Executive Management Marketo Information Technology (IT) Business Intelligence Competency Center Finance Marketing and Sales

Figure 49 – Third-party data connectors for cloud BI by function

In 2017, Large organizations of 1,001-5,000 employees and mid-sized organizations with 101-1,000 employees are most likely to embrace data connectors to Google Analytics and Salesforce (fig. 50). Small organizations (1-100 employees), often first movers in demand for cloud BI connectors, lead 2017 demand for cloud storage/sharing services Google Drive and Dropbox along with Twitter. To a lesser extent, Facebook and Windows Azure connectors are most sought by very large organizations (> 5,000employees).

Third-Party Data Connectors for Cloud BI by Organization Size Google Analytics VKontakte100% Salesforce radian6 Google Drive 90% Freshbooks 80% Facebook 70% New Relic Dropbox 60% 50% Majestic SEO LinkedIn 40% 30% Searchmetrics 20% SurveyMonkey 10% Optimizely 0% Twitter

Windows Azure Webtrends SQL

Foursqaure Google AdWords

Pingdom Google+

Eloqua YouTube

HubSpot MailChimp Zendesk Instagram Marketo 1-100 101-1000 1001-5000 More than 5000

Figure 50 – Third-party data connectors for cloud BI by organization size

Cloud Business Intelligence Licensing Interest in a range of cloud business intelligence licensing models has grown slowly and mostly in favor of subscription models over the six years of our study (fig. 51). In 2017, free trial (trial and buy), an indicator of early-stage adoption and experimentation, remains the first choice among respondents. Subscription license and managed service are the next most popular, ahead of perpetual license and maintenance, which has slowly declined as a licensing preference. The limited free-trial freemium model is somewhat less popular and used more in evaluation than production systems. On- premises options have not gathered momentum as we might have expected.

Cloud BI Licensing Preferences 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Free trial (try and buy)

Subscription license

Managed service

Perpetual license + annual maintenance

Freemium (limited free version)

On-premises option

Pay per use

Critical Very important Important Somewhat important Not important

Figure 51 – Cloud BI licensing preferences

Preference for cloud BI licensing models in 2017 varies by geography (fig. 52). North American respondents most prefer free trial and buy, followed by subscription license and managed service. Among Asia-Pacific respondents, the top choice is managed service, followed by subscription license, and free trial and buy. EMEA respondents (somewhat less enthusiastically), are most likely to prefer subscription, followed by free trial and buy, freemium, and on-premises. Latin American respondents, perhaps because of their experience with perpetual licenses and maintenance, are most likely to choose free trial and buy options.

Cloud BI Licensing Preferences by Geography 5

4.5

3.5

2.5

1.5

1 Free trial (try Subscription Managed Perpetual Freemium On-premises Pay per use and buy) license service license + annual (limited free option maintenance version)

North America Asia Pacific Europe, Middle East and Africa Latin America

Figure 52 – Cloud BI licensing preference by geography

In 2017, free trial (try and buy) licensing is most popular with Marketing/Sales, followed by the BICC and IT (fig. 53). Marketing/Sales is also most accustomed to perpetual license/maintenance licensing. BICC respondents lead interest in subscription licenses, on-premises and pay per use, while managed services are slightly more preferred by executive management.

Cloud BI Licensing Preferences by Function

Free trial (try and buy) 5 4.5 4 Pay per use 3.5 Subscription license 3 2.5 2 1.5 1

On-premises option Managed service

Freemium (limited free Perpetual license + annual version) maintenance

Executive Management Marketing and Sales Information Technology (IT) Finance Business Intelligence Competency Center

Figure 53 – Cloud BI licensing preferences by function

Organization size affects preferences for cloud BI licensing options (fig. 54). After free trial and buy, we are not surprised to see very large organizations (> 5,000 employees) most accustomed to perpetual licenses, managed services, and on-premises deployment. Small organizations (1-100 employees) have the greatest propensity to use free trial and buy and pay per use, while mid-sized organizations (101-1,000 employees) lead interest in subscription licenses and are also likely to deploy on premises.

Cloud BI Licensing Preferences by Organization Size 5

4.5

3.5

2.5

1.5

1 Free trial (try Subscription Managed Perpetual Freemium On-premises Pay per use and buy) license service license + annual (limited free option maintenance version)

1-100 101-1000 1001-5000 More than 5000

Figure 54 – Cloud BI licensing preferences by organization size

Cloud BI Hosting Preferences In 2017, we asked respondents to describe cloud BI hosting preferences through BI/analytics vendors versus third party cloud-service providers (fig. 55). While 43 percent of respondents expressed no preference, more (32 percent) chose BI/analytics vendors over third party cloud-service providers (25 percent). This finding is interesting in the context of packaging by large third-party vendors versus the economics of hosting by proprietary vendors, though semantically this might be an issue of branding.

Cloud BI Hosting Preferences

BI/analytics software vendor proprietary No preference, 43% hosting, 32%

Third-party cloud service provider, 25%

Figure 55 – Cloud BI hosting preferences

North American respondents are most likely to prefer cloud BI hosting through BI/analytics vendors (fig. 56). Asia-Pacific and EMEA respondents have almost identical profiles that prefer hosting through BI/Analytics providers, though majorities in both regions express no preference. Only respondents in Latin America prefer third-party service providers over other the BI/analytic vendor option.

Cloud BI Hosting Preferences by Geography

North America

Asia Pacific

Europe, Middle East and Africa

Latin America

0% 20% 40% 60% 80% 100%

BI/analytics software vendor proprietary hosting Third-party cloud service provider No preference

Figure 56 – Cloud BI hosting preferences by geography

BICC respondents, who generally reflect organizational best practices, are most likely to choose cloud BI hosting through BI/analytics vendors (fig. 57), and in a sense this might reflect a charter of tool preferences versus service offerings. Marketing/Sales and IT are most likely to express no preference. Executive Management and, interestingly, Finance are most open to third-party cloud provider hosting.

Cloud BI Hosting Preferences by Function

Business Intelligence Competency Center

Finance

Information Technology (IT)

Marketing and Sales

Executive Management

0% 20% 40% 60% 80% 100%

BI/analytics software vendor proprietary hosting Third-party cloud service provider No preference

Figure 57 – Cloud BI hosting preferences by function

Large organizations of 1,001-5,000 employees are by far the most likely to refer cloud BI hosting through BI/analytics vendors (fig. 58). Very large organizations (> 5,000 employees) also prefer BI/analytic provider hosting over third-party cloud-service providers, though a large majority of over 60 percent express no preference. As we might expect, small organizations (1-100 employees) and mid-sized organizations (101- 1,000 employees), most open to third party cloud-service providers, are most likely to choose them for cloud BI hosting.

Cloud BI Hosting Preferences by Organization Size

More than 5000

1001-5000

101-1000

1-100

0% 20% 40% 60% 80% 100%

BI/analytics software vendor proprietary hosting Third-party cloud service provider No preference

Figure 58 – Cloud BI hosting preferences by organization size

In 2017, industry preferences for cloud BI hosting by BI analytics/vendors are strongest in Healthcare, Higher Education, Technology and Manufacturing (fig. 59). Third-party cloud service provider hosting is most popular in Business Services, Manufacturing, and Financial Services. Retail/Wholesale and Education are most likely to have no preference.

Cloud BI Hosting Preferences by Industry 100%

90%

80%

70%

60% BI/analytics software vendor proprietary 50% hosting

40% Third-party cloud service provider 30% No preference 20%

10%

Figure 59 – Cloud BI hosting preferences by industry

Cloud BI Provider Preference In 2017, we asked respondents to rank their preferred third-party cloud BI provider (fig. 60). Seventy-three percent of respondents named AWS as their first choice, compared to 27 percent whose first choice is Google Cloud or Microsoft Azure. Google Cloud was the most popular second choice, followed by Microsoft Azure, while IBM Bluemix trailed all the offerings sampled.

Cloud BI Provider Preference

100%

90%

80%

70% First 60% Second

50% Third

40% Fourth Fifth 30%

20%

10%

0% Amazon Web Services (AWS) Google Cloud Microsoft Azure IBM Bluemix

Figure 60 – Cloud BI provider preference

Industry and Vendor Analysis

Industry and Vendor Analysis Over the last five years of our vendor analysis, industry sentiment toward cloud BI grew generally but unevenly. In our 2017 sample of cloud BI vendors, none continue to say that cloud BI is "not important," and fewer say cloud BI is only "somewhat important" (fig. 61). By comparison, more vendors (66 percent) say cloud BI is "critically important," and a steady number call cloud BI "very important." If not an absolute imperative, we believe the cloud vendor community is sure that service-based BI offerings are a required and inevitably encroaching delivery model. This finding well supports current user sentiment (fig. 8, p. 22).

Industry Importance of Cloud BI 2013-2017 70% 66% 64% 62% 61% 60% 56%

50%

40%

29% 30% 24%23%24% 21% 20% 18%

11% 11%12%11% 10% 4% 5% 0% 0% 0% Critically important Very important Somewhat important Not important

2013 2014 2015 2016 2017

Figure 61 – Industry importance of cloud BI 2013-2017

Over time, industry support for public versus private cloud business intelligence has converged, diverged, and converged again (fig 62). Following a 2015 intersection, industry support for public over private cloud grew in 2016, and in 2017, both offerings are about evenly popular. In the current year, support for private and hybrid industry investment in private and hybrid model grew as public cloud support flattened. We continue to believe all models are viable and require industry support going forward. (Also see user plans for cloud BI by deployment model, fig. 20, p. 34).

Industry Support for Cloud Business Intelligence 2012-2017 90%

80%

70%

60%

50%

40%

30%

20% 2012 2013 2014 2015 2016 2017

Public cloud Private cloud Hybrid

Figure 62 – Industry support for cloud BI 2012 to 2017

Eighty-two percent of industry respondents say public cloud is available today, compared to 76 percent for private and 71 percent for hybrid models (fig. 63). These findings are almost identical to 2016 public and private cloud availability, though hybrid offerings grew 5 percent year over year. Forward 12-month and 24-month projections also focus on hybrid over other cloud BI offerings.

Industry Availability/Plans for Cloud Business Intelligence 2017-2019 90%

80%

70%

60%

50%

40%

30%

20%

10%

0% Available today 12 months 24 months No plans

Public cloud Private cloud Hybrid

Figure 63 – Industry availability/plans for cloud BI 2017-2019

Existing industry support for business intelligence is robust in 2017 (fig. 64). Mainstay functionalities (ad-hoc query, dashboards, reporting, data visualization, and DI/DQ) are fully supported by vendors. Current vendor support diminishes dramatically only toward the end of the spectrum (cognitive computing, natural-language processing, streaming data analysis, CEP, text analytics). This finding appears to well accommodate end-user feature requirements (fig. 29, p. 43).

Industry Support for Business Intelligence Features: Current and Future 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

Cloud BI Today Cloud BI Future

Figure 64 – Industry support for BI features: current and future

Across the last four years of our study, industry support increased for all top features and remained steady or grew for several others (fig. 65). The fastest gainers are data mining/advanced algorithms, big data, and end-user data blending. Custom CSS features declined slightly over time. (For 2017, we added industry coverage of content catalog features.)

Industry Support for Cloud Business Intelligence Features: 2014-2017 120%

100%

80%

60%

40%

20%

2014 2015 2016 2017

Figure 65 – Industry support for cloud BI features 2014-2017

We asked industry respondents to describe their support for cloud-based BI versus traditional business intelligence features (fig. 66). In 2017, our entire industry sample is generally more aligned with cloud BI than with traditional BI, with some exceptions. While cloud BI offerings more notably support areas including embedded BI, data visualization, dashboards, and ad-hoc query, traditional BI offerings are more likely to support streaming data analysis, text analytics, and complex event processing. Though end-user investment also slightly favors public cloud investment today (fig. 20, p. 34), we expect all deployment models to remain important going forward.

Industry Support for Cloud Business Intelligence Features versus Traditional BI 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

Traditional BI Today Cloud BI Today

Figure 66 – Industry support for cloud BI features versus traditional BI

For the most part, the industry vendor community currently supports the cloud BI architectures that the user community needs and wants today (fig. 67). The top five requested features will be near or above 90 percent support within 12 months. The largest 12-month industry investments address multi-tenancy and real-time query to third-party cloud applications and data sources. These findings are somewhat aligned with user preferences (fig. 36, p. 50).

Industry Support and Plans for Cloud Business Intelligence Architectural Features 2017-2019 100% 90% 80% 70% 60% 50% 40% 30% 20% No plans 10% 24 months 0% 12 months Today

Figure 67 – Industry support and plans for cloud BI architectural features 2017-2019

Across the last four years of our study, industry support for cloud business intelligence architecture features climbed to all-time highs for top support areas and declined somewhat for lesser support features (fig. 68). The fastest gainer in 2017 is support for NoSQL sources. Support decreases across our industry sample are most notable in multidimensional database, multi-tenancy, and automatic upgrade support.

Industry Cloud Business Intelligence Architecture Support 2014-2017 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

2014 2015 2016 2017

Figure 68 – Industry cloud BI architecture support 2014-2017

For a second year, we asked vendor industry respondents to describe their support for desktop versus cloud-based administration and design (fig. 69). Seventy-three percent have a pure cloud-based administration and design facility; 27 percent still require desktop-based administration and design tools. This finding is an indication of whether admin capabilities are repurposed from enterprise software (requiring a remote fat client) or built from scratch for management from a browser or other Web-connected device.

Industry Support for Desktop versus Cloud-Based Adminstration and Design 80% 73% 70%

60%

50%

40%

30% 27%

20%

10%

0% Pure cloud-based administration and design Desktop-based administration and design

Figure 69 – Industry support for desktop versus cloud-based administration and design

Industry support for cloud security standards and extensions grew in 2017, though compliance remains concerning in that only one of the standards we polled has 50 percent industry support today (fig. 70). PCI/DSS and SOC Type 2 standards are most targeted for investment in 12- and 24-month time frames. However, industry respondents say five of the eight standards we polled are targeted by less than 60 percent overall support in the future. This finding is not especially aligned with user preferences, which admittedly remain even less required or understood (fig. 42, p. 56).

Business Intelligence Industry Support and Plans for Cloud Security 2017-2019

FIPS 140-2 (Federal Information Processing Standard) PCI DSS (Payment Card Industry Data Security Standard) ISO 27001 (Specification for Information Security Management System)

SAS 70 AICPA Auditing Standard (now SSAE 16)

FISMA (Federal Information Security Management Act )

TRUSTe

SOC 2 TYPE 2

HIPAA (The Health Insurance Portability and Accountability Act)

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Today 12 months 24 months No plans

Figure 70 – BI industry support and plans for cloud security 2017-2019

Ninety-two percent of all vendors we sampled currently offer cloud BI subscription models, and 98 percent plan to do so within 24 months (fig. 71). Free trial and on- premises licensing are less saturated, though vendors are planning greater 12-month rollouts for these models, which likely reflects user requests or marketing plans. Freemium has low (< 40 percent) current support but is targeted for the greatest 12- month investment. Pay-per-use models have the least current support with some 24- month investment plans. This finding is well in line with user preferences (fig. 51, p. 65).

Business Intelligence Industry Cloud Licensing 2017-2019

Subscription license

Free trial (try and buy)

On premise option

Managed service

Perpetual license + annual maintenance

Freemium (limited free version)

Pay-per use

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Today 12 months 24 months No plans

Figure 71 – Business Intelligence industry cloud licensing 2017-2019

Across four years of data, the most penetrated industry licensing model is subscription license (fig. 72). Over time, vendors directed more incremental investment toward free trial models. Managed service models grew to an all-time high while perpetual license/maintenance models steadily decreased over time. Neither freemium nor pay- per-use models gathered momentum since our 2016 study.

Industry Licensing Options for Cloud BI 2014- 2017 100%

90%

80%

70%

60% 2014 50% 2015 40% 2016 2017 30%

20%

10%

0% Subscription Free trial (try On-premises Managed Perpetual Freemium Pay per use license and buy) option service license + annual (limited free maintenance version)

Figure 72 – Industry licensing options for cloud BI 2014-2017

Industry support for third-party data sources is by far strongest for Salesforce (> 90 percent) and Google Analytics (> 70 percent) (fig.73). The next most-supported third- party data sources are Twitter (50 percent), Windows Azure SQL (47 percent), and Facebook (41 percent). These findings are somewhat in line with user preferences, which are led by Google Analytics, followed by Salesforce and personal productivity services Google Drive and Dropbox (fig. 47, p. 61).

Industry Support for Third-Party Data Sources 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Salesforce Google Analytics Twitter Windows Azure SQL Facebook Google Drive Marketo Eloqua Zendesk LinkedIn Dropbox Google AdWords HubSpot MailChimp radian6 Freshbooks Instagram Survey Monkey YouTube New Relic Optimizely Webtrends Foursquare Google+ Pingdom Searchmetrics

Figure 73 – Industry support for third-party data sources

Cloud Business Intelligence Vendor Ratings In rating the vendors, we considered cloud BI features, cloud architecture, cloud security, and Web data connectors, as reported by suppliers and weighted by user priority of capabilities (fig. 74). We also emphasize public-cloud deployment options (e.g., multi-tenancy).

Top vendors include Domo (1st), Salesforce (2nd), GoodData (3rd), SAP (3rd), Microsoft (4th) and Information Builders (5th).

Cloud Business Intelligence Vendor Ratings Domo Infor 128 Salesforce Jedox 64 GoodData 32 16 Looker SAP 8 4 Zoomdata 2 Microsoft 1 1 TIBCO Software 0 Information Builders 0

Logi Analytics Inc Oracle

Tableau IBM

Pentaho Qlik

Pyramid Analytics OpenText Yellowfin Klipfolio Inc.

Features Architecture Web data connectors Security Score Overall score

Figure 74 – Cloud business intelligence vendor ratings

Other Dresner Advisory Services Research Reports

- Wisdom of Crowds “Flagship” Business Intelligence Market study - Advanced and Predictive Analytics - Analytical Data Infrastructure - Big Data Analytics - Business Intelligence Competency Center - Collective Insights® - End User Data Preparation - Enterprise Planning - Internet of Things and Business Intelligence - Location Intelligence - Natural Language Analytics - Small and Mid-Sized Enterprise Business Intelligence

Appendix: Cloud BI User Survey Instrument

Please enter your contact information below

First Name*: ______

Last Name*: ______

Title: ______

Company Name*: ______

Street Address: ______

City: ______

State: ______

Zip: ______

Country: ______

Email Address*: ______

Phone Number: ______

URL: ______

What major geography do you reside in?*

( ) North America

( ) Europe, Middle East and Africa

( ) Latin America

( ) Asia Pacific

Please identify your primary industry*

( ) Advertising

( ) Aerospace

( ) Agriculture

( ) Apparel & accessories

( ) Automotive

( ) Aviation

( ) Biotechnology

( ) Broadcasting

( ) Business services

( ) Chemical

( ) Construction

( ) Consulting

( ) Consumer products

( ) Defense

( ) Distribution & logistics

( ) Education (Higher Ed)

( ) Education (K-12)

( ) Energy

( ) Entertainment and leisure

( ) Executive search

( ) Federal government

( ) Financial services

( ) Food, beverage and tobacco

( ) Healthcare

( ) Hospitality

( ) Insurance

( ) Legal

( ) Manufacturing

( ) Mining

( ) Motion picture and video

( ) Not for profit

( ) Pharmaceuticals

( ) Publishing

( ) Real estate

( ) Retail and wholesale

( ) Sports

( ) State and local government

( ) Technology

( ) Telecommunications

( ) Transportation

( ) Utilities

( ) Other - Please specify below

How many employees does your company employ worldwide?

( ) 1-100

( ) 101-1,000

( ) 1,001-2,000

( ) 2,001-5,000

( ) 5,001-10,000

( ) More than 10,000

What function do you report into?*

( ) Business Intelligence Competency Center

( ) Executive management

( ) Faculty (Education)

( ) Finance

( ) Human resources

( ) Information Technology (IT)

( ) Manufacturing

( ) Marketing

( ) Medical staff (Healthcare)

( ) Operations

( ) Research and development (R&D)

( ) Sales

( ) Strategic planning function

( ) Supply chain

( ) Other - Write In

Does your organization use or intend to use cloud-based BI / analytics?

( ) Yes. We use Cloud-based BI/ Analytics today

( ) No. We have no plans to use Cloud-based BI/ Analytics at all.

( ) We are currently evaluating Cloud-based BI/ Analytics software

( ) We may use Cloud-based BI/ Analytics in the future

What are your organization's plans for cloud-based BI / analytics applications?

Plan Plan to to Using No use use Discontinued today plans this next year year

Public ( ) ( ) ( ) ( ) ( ) cloud BI

Hybrid ( ) ( ) ( ) ( ) ( ) cloud BI

Private ( ) ( ) ( ) ( ) ( ) cloud BI

Does your organization have a preference for where BI / analytics functionality is hosted in the cloud?

( ) BI/analytics software vendor proprietary hosting

( ) Third-party cloud service provider

( ) No preference

Which cloud service providers does your organization have a preference for?

Importance

Amazon ______Web Services (AWS)

Google ______Cloud

IBM ______Bluemix

Microsoft ______Azure

Where will your organization increase, decrease or maintain cloud-based Business Intelligence / analytics investments?

Increase Decrease Maintain Discontinue

Public ( ) ( ) ( ) ( ) cloud BI

Hybrid ( ) ( ) ( ) ( ) cloud BI

Private ( ) ( ) ( ) ( ) cloud BI

For the feature set below, please indicate which are required for "cloud" BI user solutions.

Very Somewh Critic Importa Unimporta importa at al nt nt nt important

Ability to write to ( ) ( ) ( ) ( ) ( ) transactional applications

Ad-hoc query ( ) ( ) ( ) ( ) ( )

Advanced ( ) ( ) ( ) ( ) ( ) visualization

Big data (e.g., ( ) ( ) ( ) ( ) ( ) Hadoop) support

Collaborative ( ) ( ) ( ) ( ) ( ) support for group- based analysis

Complex event ( ) ( ) ( ) ( ) ( ) processing (CEP)

Data catalog ( ) ( ) ( ) ( ) ( )

Data discovery ( ) ( ) ( ) ( ) ( )

Data integration / ( ) ( ) ( ) ( ) ( ) data quality tools/ETL

Data mining and ( ) ( ) ( ) ( ) ( ) advanced algorithms

End-user data ( ) ( ) ( ) ( ) ( ) blending or "mashups"

End-user "self- ( ) ( ) ( ) ( ) ( ) service"

In-memory support ( ) ( ) ( ) ( ) ( )

Location ( ) ( ) ( ) ( ) ( ) intelligence/analyti cs

Natural language ( ) ( ) ( ) ( ) ( ) analytics

Personalized ( ) ( ) ( ) ( ) ( ) dashboards

Prepackaged ( ) ( ) ( ) ( ) ( ) vertical/functional

analytical applications

Production ( ) ( ) ( ) ( ) ( ) reporting

Search interface ( ) ( ) ( ) ( ) ( )

Social media ( ) ( ) ( ) ( ) ( ) analysis (Social BI)

Text analytics ( ) ( ) ( ) ( ) ( )

Please check the following technical/architectural features that are required for a cloud- based BI / analytics solution.

Very Somewhat Critical Important Unimportant important important

Automatic ( ) ( ) ( ) ( ) ( ) upgrades

Cloud ( ) ( ) ( ) ( ) ( ) application connections (e.g., Salesforce, NetSuite)

Cloud ( ) ( ) ( ) ( ) ( ) database connectors (e.g., database.com, Redshift, SimpleDB, CloudSQL)

Connectors to ( ) ( ) ( ) ( ) ( ) on-premises

applications and data (e.g., ERP, CRM)

Data ( ) ( ) ( ) ( ) ( ) virtualization

Multi- ( ) ( ) ( ) ( ) ( ) dimensional database support

Multi-tenancy ( ) ( ) ( ) ( ) ( ) (single executable supporting multiple customers)

Open client ( ) ( ) ( ) ( ) ( ) connector (e.g., ODBC, JDBC)

Real-time ( ) ( ) ( ) ( ) ( ) query to third- party cloud applications, cloud data sources, and on-premises systems

Relational ( ) ( ) ( ) ( ) ( ) database support

RESTful/Web ( ) ( ) ( ) ( ) ( ) Services API

Please check all third-party data connectors that you would like a cloud BI / analytics product to connect to

[ ] Dropbox

[ ] Eloqua

[ ] Facebook

[ ] foursquare

[ ] Freshbooks

[ ] Google AdWords

[ ] Google Analytics

[ ] Google Drive

[ ] Google+

[ ] Hubspot

[ ] Instagram

[ ] LinkedIn

[ ] MailChimp

[ ] Majestic SEO

[ ] Marketo

[ ] New Relic

[ ] Optimizely

[ ] Pingdom

[ ] radian6

[ ] Salesforce

[ ] Searchmetrics

[ ] SurveyMonkey

[ ] Twitter

[ ] VKontakte

[ ] Webtrends

[ ] Windows Azure SQL

[ ] YouTube

[ ] Zendesk

[ ] Other - Write In: ______

What aspects of cloud security does your organization require from its cloud BI / analytics provider? Select all/any that apply.

[ ] ISO 27001 (Specification for Information Security Management System)

[ ] SAS 70 AICPA Auditing Standard (now SSAE 16)

[ ] HIPAA (Health Insurance Portability and Accountability Act)

[ ] FERPA (Family Educational Rights and Privacy Act)

[ ] FIPS 140-2 (Federal Information Processing Standard)

[ ] FISMA (Federal Information Security Management Act )

[ ] PCI DSS (Payment Card Industry Data Security Standard)

[ ] SOC 2 TYPE 2

[ ] TRUSTe

[ ] None

[ ] Don't know

[ ] Other - Write In: ______

Please share your organizations preferences for licensing and implementation related to cloud BI.

Very Somewhat Not Critical Important important important important

Free trial (try ( ) ( ) ( ) ( ) ( ) and buy)

Freemium ( ) ( ) ( ) ( ) ( ) (limited free version)

Managed ( ) ( ) ( ) ( ) ( ) service

On premises ( ) ( ) ( ) ( ) ( ) option

Pay per use ( ) ( ) ( ) ( ) ( )

Perpetual ( ) ( ) ( ) ( ) ( ) license + annual maintenance

Subscription ( ) ( ) ( ) ( ) ( ) license

What do you see as the primary benefits/advantages and barriers/limitations of cloud BI / analytics?

Benefits/ advantages: ______

Barriers/ limitations: ______