September 30, 2015
Dresner Advisory Services, LLC
2015 Edition
Small and Mid-Sized Enterprise
Business Intelligence Market
Study
Wisdom of Crowds® Series
Licensed to Klipfolio
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Disclaimer
This report should be used for informational purposes only. Vendor and product selections should be made
based on multiple information sources, face-to-face meetings, customer reference checking, product
demonstrations, and proof-of-concept applications.
The information contained in all Wisdom of Crowds® Market Study Reports reflects the opinions expressed
in the online responses of individuals who 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 reports, study results, or for any damages incurred or alleged to be incurred by any of the companies
included in the reports as a result of its content.
Reproduction and distribution of this publication in any form without prior written permission is forbidden.
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Business Intelligence: A Definition
We define Business intelligence (BI) as “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)
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Introduction
This year we celebrate the eighth anniversary of Dresner Advisory Services! Our thanks
to all of you that have been with us along the way, encouraging and challenging us!
Since our founding in 2007, we have strived to offer a fresh, real-world and alternative
perspective on the Business Intelligence (BI) market. We hope that you agree that we
not only have succeeded in doing so but also continue to “raise the bar”—offering
increasingly compelling research and greater value with each successive year!
Since we published our first Wisdom of Crowds® Business Intelligence Market study in
2010, we have continued to expand our research offerings to include a variety of
important topics including: Location Intelligence, Advanced and Predictive Analytics,
Cloud Computing and BI, Collaborative Computing and BI, Embedded BI, BI Emerging
Technologies, and Small & Mid-Sized Enterprise BI. During 2015 we added to these
topics with coverage for Enterprise Planning, End-User Data Preparation, Internet of
Things (IoT), and Big Data Analytics.
For this, our third SME market study report, we created a focused, detailed report
examining business intelligence in small and mid-sized organizations. In particular, we
consider how their deployments and views differ from each other and from larger
organizations. Also included are two new models for examining and understanding the
vendor landscape within the SME business intelligence market and a buyer’s guide for
22 BI software vendors.
In closing, we’re very excited about both the market and our ability to continue to add
substantial perspective and value to it!
Thanks for your support!
Best,
Howard Dresner
Chief Research Officer
Dresner Advisory Services
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Contents
Business Intelligence: A Definition .................................................................................. 3
Introduction ..................................................................................................................... 4
Benefits of the Study ....................................................................................................... 7
A Consumer Guide ...................................................................................................... 7
A 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 Collection........................................................................................................... 10
Data Quality ............................................................................................................... 11
Executive Summary ...................................................................................................... 13
Study Demographics ..................................................................................................... 14
Geography ................................................................................................................. 14
Functions ................................................................................................................... 15
Vertical Industries ...................................................................................................... 16
Analysis and Trends ...................................................................................................... 18
How SMEs Differ ........................................................................................................... 19
Technology Priorities Changing ................................................................................. 19
Departments/Functions Driving Business Intelligence ............................................... 21
Departmental Drivers .............................................................................................. 21
User Roles Targeted for Business Intelligence .......................................................... 23
Objectives for Business Intelligence .......................................................................... 25
Business Intelligence Objectives by Function ......................................................... 27
Penetration of Business Intelligence .......................................................................... 28
SME Success with Business Intelligence ................................................................... 31
State of Data .............................................................................................................. 32
Action on Insight ........................................................................................................ 33
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Introduced in 2014, Action on Insight is Dresner Advisory’s high-level self-assessment
of BI best (and worst) practices.................................................................................. 33
Business Intelligence Market Models for SMEs ............................................................ 35
Customer Experience Model for SMEs ...................................................................... 35
Vendor Credibility Model for SMEs ............................................................................ 37
Business Intelligence Buyers’ Guide ............................................................................. 39
Cloud Platform Support Vendors (A – D) ................................................................... 39
Mobile Platform Support Vendors (A – D) .................................................................. 40
Traditional Platform Support Vendors (A – D) ............................................................ 41
Cloud Platform Support Vendors (I – K)..................................................................... 42
Mobile Platform Support Vendors (I – K) ................................................................... 43
Traditional Platform Support Vendors (I – K) ............................................................. 44
Cloud Platform Support Vendors (L – M) ................................................................... 45
Mobile Platform Support Vendors (L - M) ................................................................... 46
Traditional Platform Support Vendors (L - M)............................................................. 47
Cloud Platform Support Vendors (O - Q) ................................................................... 48
Mobile Platform Support Vendors (O - Q) .................................................................. 49
Traditional Platform Support Vendors (O - Q) ............................................................ 50
Cloud Platform Support Vendors (R - S) .................................................................... 51
Mobile Platform Support Vendors (R - S) ................................................................... 52
Traditional Platform Support Vendors (R - S)............................................................. 53
Cloud Platform Support Vendors (T - Y) .................................................................... 54
Mobile Platform Support Vendors (T - Y) ................................................................... 55
Traditional Platform Support Vendors (T - Y) ............................................................. 56
Appendix - The 2015 Wisdom of Crowds® Business Intelligence Market Survey
Instrument ..................................................................................................................... 57
Other Dresner Advisory Services Research Reports .................................................... 69
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Benefits of the Study
The DAS Small and Mid-Sized Enterprise Business Intelligence Market Study provides
a wealth of information and analysis—offering value to both consumers and producers
of Business Intelligence technology and services.
A Consumer Guide
As an objective source of industry research, consumers use the DAS Small and MidSized Enterprise Business Intelligence Market Study to understand how their peers use
and invest in Business Intelligence and related technologies.
Using our trademarked 33-dimension vendor performance measurement system, users
glean key insights into BI software supplier performance, enabling:
Comparisons of current vendor performance to industry norms
Identification and selection of new vendors
A Supplier Tool
Vendor Licensees can use the DAS Small and Mid-Sized Enterprise Business
Intelligence Market Study in several important ways, for example to:
External Awareness
- Build awareness for the Business Intelligence market and supplier brand, citing The
DAS Small and Mid-Sized Enterprise Business Intelligence Market Study trends and
vendor performance
- Create lead and demand-generation for supplier offerings through association with
The DAS Small and Mid-Sized Enterprise 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 Small and Mid-Sized Enterprise Business Intelligence Market
Study
- Better understand customer priorities, concerns, and issues
- Identify competitive pressures and opportunities
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
About Howard Dresner and Dresner Advisory Services
The DAS Small and Mid-Sized Enterprise Business Intelligence 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
- Cloud Computing and Business Intelligence
- Collaborative Computing and Business Intelligence
- End User Data Preparation
- Internet of Things and Business Intelligence
Howard (www.twitter.com/howarddresner) conducts a weekly Twitter “tweetchat” on
Fridays at 1:00 p.m. ET. The hashtag is #BIWisdom. 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.
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
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.
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Survey Method and Data Collection
For this SME study, we sampled different subsets of the 2015 Wisdom of Crowds
Business Intelligence Market Survey. Dresner Advisory Services defines “Small
Enterprise” as an organization with between one and 100 employees; “Mid-Sized
Enterprise” an organization with between 101 and 1,000 employees; and “Large
Enterprise” as an organization with more than 1,000 employees. We constructed the
study from a survey instrument to collect data and used social media and
crowdsourcing techniques to recruit participants.
Data Collection
A total of 778 surveys (versus 717 in 2014) were submitted by small and mid-sized
(SME) organizations. This report focuses on the responses of those SME organizations
and draws comparisons between their responses and those of the full sample.
SME Study Sample
700
617
600
500
418
400
360
300
200
100
0
Small (1-100)
Mid (101-1000)
Large (1000+)
Figure 1 – SME study sample
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Data Quality
We carefully scrutinized and verified all respondent entries to ensure that the study
includes only qualified participants.
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Executive
Summary
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Executive Summary
Much like larger organizations, small and medium-sized enterprises prioritize a wide
span of BI technologies and initiatives (p. 19).
SME technology priorities have remained remarkably consistent across three years
of study with only minor changes in priority (p. 20).
Executive management and sales are the strongest functional drivers at SMEs
(slightly more so than at large enterprises). SME drivers have remained consistent
across three years of study (pp. 21-22).
Small and mid-sized enterprises target executives slightly more often than their
large-enterprise peers, which are much more likely to target managers. SMEs are
slowly moving to target more individual contributors (pp. 23-24).
BI objectives, led by “better decision making,” are largely consistent across
organizations of different sizes (p. 25).
"Better decision-making," "growth in revenues," "increased competitive advantage,"
and "enhanced customer service" all gained as SME 2015 BI objectives (p. 26).
SMEs in 2015 report much higher levels of business intelligence penetration than
larger organizations (p.28).
Small and mid-sized organizations plan modest development from current levels in
the next 12 months that will accelerate in future timeframes (p. 29).
SMEs report somewhat disappointing degrees of improved BI penetration in 2014 to
2015 (p. 30).
Reports of "complete success" with BI are most likely in small organizations and
decrease with organization size (p. 31).
An organization's opinion of the state of data governance and consistency
decreases as the size of the organization increases (p. 32).
As might be expected, SMEs are somewhat more likely to claim an ability to execute
with "closed loop” processes for action on insight (p. 33).
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Study Demographics
The respondents studied in this SME survey provide a cross-section of data by
geography, function, organization size, and vertical industries. We believe this supports
a representative sample and indicator of true market dynamics. We constructed crosstab analyses using these demographics to identify and illustrate important industry
trends.
Geography
Forty-nine percent of respondents are located in North America, which includes the
United States, Canada, and Puerto Rico (fig. 2). EMEA organizations represent 28
percent of respondents. Asia Pacific (10 percent) and Latin America (6 percent) are the
other regions represented.
Geographies of SMEs Represented
Latin
America,
6%
Asia Pacific, 10%
North America, 49%
Europe, Middle East,
& Africa, 28%
Figure 2 - Geographies of SMEs represented
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Functions
Information technology (23 percent) and executive management (20 percent) are the
functions most represented in the study. Thirteen percent of respondents represent
finance and 12 percent represent Business Intelligence Competency Centers (BICCs),
which in the SME market can include dedicated BI resources as well as formal
organizational departments (fig. 3). Our sample is somewhat more balanced than in
2014 when one-third of respondents were information workers in IT.
This distribution across functions enables us to develop analyses comparing and
contrasting the plans and priorities of the different departments within organizations.
Functions of SMEs Represented
25%
23%
20%
20%
15%
13%
12%
10%
5%
5%
4%
4%
3%
3%
3%
2%
0%
Figure 3 - Functions of SMEs represented
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Vertical Industries
Vertical industry distribution among SMEs is led by technology and consulting and
includes a diverse cross-section of education, retail, and manufacturing organizations
among other private and public institutions (fig. 4).
SME Vertical Industries Represented
30.0%
25%
25.0%
20.0%
17%
15.0%
14%
10.0%
5.0%
5% 5%
4% 4% 3%
3% 2%
2% 2% 2% 2%
1% 1% 1% 1% 1% 1% 1% 1%
0.0%
Figure 4 – SME vertical industries represented
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Analysis and
Trends
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Analysis and Trends
This report describes the Small and Mid-Sized Enterprise market for Business
Intelligence by its own characteristics, drivers, and trends, and also by how it compares
to the large enterprise market.
In 2015 we sampled SME experience with business intelligence including the uptake of
technologies and future plans year over year. As in the larger Wisdom of Crowds study,
we collected and analyzed data for SMEs surrounding functions driving business
intelligence, goals/objectives for BI, targeted user roles, current penetration, and future
plans for business intelligence deployment and organizational success.
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
How SMEs Differ
Technology Priorities Changing
Much like larger organizations, small and medium-sized enterprises prioritize a wide
span of BI technologies and initiatives (fig. 5). Top priorities in common are dashboards,
end-user self-service, advanced visualization, and integration with operational systems.
SME interest in other BI technologies differs in part due to complexity, total cost of
ownership, and time to value. Smaller organizations show considerably less interest in
data warehousing than large peers. Small organizations are considerably more
interested in software as a service / cloud computing and slightly more interested in
mobile device support. Smaller organizations are somewhat less likely to embrace big
data, data mining, and location intelligence but are slightly more interested in social BI.
Technology Priorities: SMEs versus Large Enterprises
Cognitive BI (e.g., Artificial
Intelligence-based
BI)
Complex event
processing
(CEP)
Internet of things (IoT)
Open source software
Social media analysis
(SocialBI)
Text analytics
Dashboards
End user "self service"
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
Advanced visualization
Integration with
operational processes
Data warehousing
Data discovery
Enterprise
planning/budgeting
Ability to write to
transactional applications
Mobile device support
Data mining, advanced
algorithms, predictive
Big Data (e.g., Hadoop)
Pre-packaged
vertical/functional…
Embedded BI (contained
within an application,…
Software-as-a-service and
cloud computing
End user data "blending"
Collaborative support
for
(data mash ups)
group-based analysis
Search-based interface
In-memory analysis
Location
intelligence/analytics
SME
LGE
Figure 5 - Technology priorities: SMEs versus large enterprises
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
SME technology priorities remain remarkably consistent across three years of study
with only minor changes in priority (fig. 6). We believe this reflects good market
awareness and thoughtful, if cautious, planning in response to BI provider marketing
and industry trends. Though differences are small, if anything, BI interest appears to
have peaked in several categories and declined slightly in areas that include
cloud/SaaS, end user self-service, and pre-packaged vertical apps. That said, average
interest in most categories hovers near 3.5 or higher, placing them between “important”
and “very important.”
Technology Priority Changes 2013 to 2104: SME versus
Overall Sample
Complex Event Processing
(CEP)
Open Source Software
Social media Analysis
(SocialBI)
Text Analytics
Ability to write to
transactional applications
Dashboards
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
End user "self service"
Advanced visualization
Integration with Operational
Processes
Data Warehousing
Data Discovery
Big Data (e.g., Hadoop)
Mobile Device Support
Pre-packaged
vertical/functional…
Data Mining, Advanced
Algorithms, Predictive
Embedded BI (contained
within an application,…
Search-based interface
In-memory analysis
Collaborative Support for
Group-based Analysis
Location
Intelligence/Analytics
2013
2014
End user data "blending"
(data mash ups)
Software-as-a-Service and
"Cloud" Computing
2015
Figure 6 – Technology priority changes 2013 to 2015: SME versus overall sample
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Departments/Functions Driving Business Intelligence
Our 2015 survey looks at the functions that drive business intelligence initiatives within
the organization. For each function, we asked respondents to specify whether it drives
business intelligence “always,” “often,” “sometimes,” “rarely,” or “never.” We used this to
create a weighted average on a zero-to-five scale.
Departmental Drivers
Executive management and sales are the strongest functional drivers at SMEs and
slightly more so than at large enterprises (fig. 7). Smaller organizations are also more
likely to be driven by strategic planning, marketing, and R&D, which might imply a
product or project emphasis (as opposed to an enterprise-wide emphasis on BI
enablement). Interestingly, organizations of different sizes have similar propensity (3.43.5, between "often" and "sometimes") to see their BI efforts driven by IT. As dictated by
their structure, SMEs are slightly less likely to be driven by finance or supply chain
functions.
Functions Driving Business Intelligence
by Organization Size
4.5
4
3.5
3
2.5
2
1.5
1
Small
Mid
Large
Figure 7 – Functions driving business intelligence by organization size
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Much like BI technology priorities, SME drivers of business intelligence remain
consistent across three years of study (fig. 8). Executive management, always the
leading driver, even gained a bit of ground, reminding us that SME leadership is the
most likely advocate in the room. Sales returned to the mean after a slight uptick in
2014. In a minor watershed event, the strategic planning function and operations slightly
surpassed IT as 2015 SME drivers.
SME Drivers of BI 2013 to 2015
4.5
4
3.5
3
2.5
2
1.5
1
2013
0.5
2014
2015
0
Figure 8 - SME Drivers of BI 2013 to 2015
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
User Roles Targeted for Business Intelligence
Our survey asked which functions/roles are targeted for automation with business
intelligence solutions. Respondents were able to designate these roles as either
“primary,” “secondary,” or “not applicable.” Among all organizations sampled, the
majority prioritized (in order) executives, middle managers, line managers, individuals,
customers, and suppliers.
Small and mid-sized enterprises target executives slightly more often than their largeenterprise peers (fig. 9). What stands out in this view is the higher (and growing)
emphasis on managerial and individual contributor ranks at large enterprises. We
expect the business structure of different sized enterprises with specific departmental
autonomy, budgets, priorities, and scope dictates this finding. Not for the first time, small
and mid-sized organizations are more likely to target customers than large
organizations.
Primary Targeted Users for Business Intelligence
by Organization Size
80%
70%
60%
50%
40%
Small
Mid
30%
Large
20%
10%
0%
Executives
Middle
managers
Line managers
Individual
contributors &
professionals
Customers
Suppliers
Figure 9 - Primary targeted users for business intelligence by organization size
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Across three years of study we observe a slight shifting of BI targeting emphasis at
SMEs (fig. 10). Executives get the most attention in 2015 as in previous years, but
slightly less so than in 2013 and 2014. With fewer BI targets atop SME management
structures, this could reflect saturation or a widening view of BI opportunities. In the
same time frame there is a corresponding increase in targeting of individual
contributors.
SME Targets for BI 2013 to 2015
90%
80%
70%
60%
50%
2013
40%
2014
2015
30%
20%
10%
0%
Executives
Middle
Managers
Line Managers
Individual
Contributors &
Professionals
Customers
Suppliers
Figure 10 - SME targets for BI 2013 to 2015
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Objectives for Business Intelligence
BI objectives as described in the survey are largely consistent across organizations of
different sizes (fig. 11). Among all organizations of any size, “better decision making” is
the most-cited objective. As organization size increases, respondents are less likely to
cite revenue growth, competitive advantage, or customer service as BI objectives. Large
organizations focus more on operational efficiency, which likely reflects the number
and/or complexity of business processes.
Business Intelligence Objectives by Organization
Size
5
4.5
4
3.5
3
2.5
2
1.5
1
Better decision
making
Improved
operational
efficiency
Growth in revenues
Small
Mid
Increased
competitive
advantage
Enhanced customer
service
Large
Figure 11 - Business intelligence objectives by organization size
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Among small and mid-sized organizations, "better decision making," "growth in
revenues," "increased competitive advantage," and "enhanced customer service" all
gained prominence as 2015 BI objectives (fig. 12). Revenue growth supplanted
"improved operational efficiencies" as the second most-cited objective in 2015.
SME BI Objectives 2014 to 2015
4.6
4.4
4.2
4
2014
3.8
2015
3.6
3.4
3.2
Better decision
making
Improved
operational
efficiency
Growth in
revenues
Increased
competitive
advantage
Enhanced
customer service
Figure 12 – SME BI objectives 2014 to 2015
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Business Intelligence Objectives by Function
Across SMEs (and also the entire sample of organizations) "better decision making" is
the perennial top BI objective of organizations. This tells us that while organizations may
face changing priorities, they have always been ready to leverage business intelligence
whenever the opportunity arises. Across functions in 2015, this tendency is as
pronounced as ever (fig. 13). Sales, with a focus upon profitable revenue growth, places
an equally high priority upon growth in revenues and improved operational efficiency.
Among trailing objectives, most functions lean toward operational efficiency, notably IT
and finance, which are most likely to be budget and cost containment minded. Even
executive management emphasizes operational efficiency over revenue growth.
Predictably, marketing is likely to emphasize revenue and competitive advantage above
operational efficiency.
Business Intelligence Objectives
by Function: SMEs Only
5
4.5
4
3.5
3
2.5
2
1.5
1
Marketing
Executive
management
Information
Technology (IT)
Sales
Finance
Business Intelligence
Competency Center
Better decision making
Improved operational efficiency
Growth in revenues
Increased competitive advantage
Enhanced customer service
Figure 13 – BI objectives by function: SMEs Only
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Penetration of Business Intelligence
As we found in earlier studies, SMEs in 2015 report much higher levels of business
intelligence penetration than larger organizations (fig. 14). Small enterprises (1-100
employees) are almost three times as likely as large organizations to report the highest
(81 percent or more) BI penetration and are considerably less likely to report the lowest
levels of penetration. Mid-sized organizations (100-1,000 employees) also consider their
BI penetration to be more mature than large peers but are not as mature with BI as
small organizations.
Current BI Penetration by Organization Size
45%
40%
35%
30%
25%
Small
Mid
20%
Large
15%
10%
5%
0%
Under 10%
11 - 20%
21 - 40%
41 - 60%
61 - 80%
81% or more
Figure 14 - Current BI penetration by organization size
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Small and mid-sized organizations plan modest BI expansion from current levels in the
next 12 months that will accelerate in future time frames (fig. 15). In small organizations,
low-level penetration (< 10 percent) will hover near 12 percent going forward, while the
highest level (81 percent or greater) will grow at about 5 percent in 24 and 36-month
time frames. Mid-sized organizations expect gradual improvements that will move from
the three lowest levels to higher BI penetration in consecutive 12, 24 and 36-month time
frames.
Planned Business Intelligence Penetration
through 2018 by Organization Size
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
In 12
months
In 24
months
In 36
months
In 12
months
In 24
months
Small
Under 10%
In 36
months
In 12
months
Mid
11 - 20%
21 - 40%
In 24
months
In 36
months
Large
41 - 60%
61 - 80%
81% or more
Figure 15 – Planned business intelligence penetration through 2018 by organization size
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
29
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
SMEs report only modest degrees of improved BI penetration 2014 to 2015 (fig. 16).
The lowest level of penetration (<10 percent) actually ticked up slightly and now
accounts for about one-third of respondents. Small improvements were seen in the 41
to 60 percent range (from 7 percent to 11 percent in 2015) with a corresponding
decrease in 11 to 20 percent penetration. The highest level (>81 percent) gained
slightly, from 18 to 19 percent.
SME BI Penetration 2014 to 2015
35%
30%
25%
20%
2014
2015
15%
10%
5%
0%
Under 10%
11 - 20%
21 - 40%
41 - 60%
61 - 80%
81% or more
Figure 16 - SME BI penetration 2014 to 2015
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
30
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
SME Success with Business Intelligence
The likelihood of reporting "complete success" with business intelligence programs and
initiatives is most pronounced in small (1-100) organizations and decreases with
organization size (fig. 17). Mid-sized (100-1,000) and larger organizations are more
likely to have mixed views of BI success, more likely to both agree and disagree
somewhat. Fewer than 3 percent of organizations of any size disagree completely that
their BI initiatives have been successful.
Success with Business Intelligence
by Organization Size
70%
60%
50%
40%
30%
20%
10%
0%
Completely agree
Agree somewhat
Small
Disagree somewhat
Mid
Disagree
Large
Figure 17 - Success with business intelligence by organization size
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
31
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
State of Data
An organization's opinion of the state of data governance and consistency decreases as
the size of the organization increases (fig. 18). Well more than one-third of closer-knit,
small (1-100) enterprises have the highest view of their governance being at the level of
“data as truth.” More than 40 percent of small and mid-sized organizations claim "a
common view of enterprise data," somewhat ahead of large organizations. Large
organizations are more likely than SMEs to report department-level or multiple
inconsistent data sources.
Business Intelligence and the State of Data
by Organization Size
Data as "truth" - A common view of enterprise data
is available with common application of data, filters,
rules and semantics
A common view of enterprise data is available.
However, parochial views and semantics are used to
support specific positions
Consistent data is available at a departmental level.
Conflicting, functional views of data causes
confusion and disagreement
We have multiple, inconsistent data sources with
conflicting semantics and data. Information is
generally unreliable and distrusted
0%
Large
Mid
5% 10% 15% 20% 25% 30% 35% 40% 45%
Small
Figure 18 – Business intelligence and the state of data by organization size
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
32
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Action on Insight
Introduced in 2014, Action on Insight is Dresner Advisory’s high-level self-assessment
of BI best (and worst) practices.
As might be expected, SMEs are somewhat more likely to claim an ability to execute
with closed loop processes (fig. 19). In the largest group, 61 percent of large, 63 percent
of mid-sized and 56 percent of small organizations report ad hoc (informal) action on
insights across functions. Just 4 percent or fewer of all organizations say they rarely
leverage insights.
Business Intelligence and Action on Insight
by Organization Size
“Closed loop processes for action” - Information is
shared, teams work to process and act in a timely
fashion. No formal boundaries
Ad hoc (informal) action on insights across functions
Uncoordinated/ parochial action (sometimes at the
expense of others)
Insights are rarely leveraged
0%
Large
Mid
10%
20%
30%
40%
50%
60%
70%
Small
Figure 19 – Business intelligence and action on insight by organization size
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
33
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
SME Vendor
Rankings
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
34
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Business Intelligence Market Models for SMEs
For 2015 we developed two new models for examining and understanding the business
intelligence market. Using quadrants, we plotted aggregated user sentiment into x and y
axes.
Customer Experience Model for SMEs
The customer experience model considers the real-world experience of customers
working with BI products on a daily basis (fig. 20). For the x axis, we combined all
vendor touch points—including the sales and acquisition process (8 measures),
technical support (5 measures), and consulting services (5 measures) —into a single
“sales and service” dimension. On the y axis, we plotted customer sentiment
surrounding product, derived from the 12 product and technology measures used to
rank vendors. On the resulting four quadrants, we plotted vendors based on these
measures.
The upper-right quadrant contains the highest-scoring vendors and is named “overall
experience leaders.” Technology leaders (upper-left quadrant) identifies vendors with
strong product offerings but relatively lower services scores. Service leaders (lower-right
quadrant) provide strong customer service with relatively lower technology scores.
Contenders (lower-left quadrant) would benefit from varying degrees of improvement to
product, services, or both.
User sentiment surrounding outliers (outside of the four quadrants) suggests that
significant improvements are required to product and services.
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
35
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Figure 20 - Customer Experience Model for SMEs
A – Dimensional Insight
B – Birst
C – TIBCO
D – RapidMiner
E – Adaptive Insights
F – Information Builders
G – Pyramid Analytics
H – Dundas
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
36
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Vendor Credibility Model for SMEs
The vendor credibility model considers how customers “feel” about their vendor (fig. 21).
The x axis plots perceived value for the price paid. The y axis combines the integrity
and recommend measures, creating a “confidence” dimension. The resulting four
quadrants position vendors based on these dimensions.
The upper-right quadrant contains the highest-scoring vendors and is named “credibility
leaders.” Value leaders (upper-left quadrant) identifies vendors with solid perceived
value but relatively lower confidence scores. Contenders (lower-left quadrant) would
benefit by working to improve customer value, confidence, or both.
User sentiment surrounding outliers (outside of the four quadrants) suggests that
significant improvements are required to improve perceived value and confidence.
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
37
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Figure 21 - Vendor Credibility Model for SMEs
A – Information Builders
B – Dimensional Insight
C – Birst
D – Pyramid Analytics
E – Yellowfin
F – RapidMiner
G – TIBCO
H – Dundas
I – Tableau Software
J – Adaptive Insights
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
38
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Business Intelligence Buyers’ Guide
In this section, we present a Business Intelligence Buyers’ Guide organized by key
platforms: traditional, cloud, and mobile. For each vendor, we share data collected for
22 different areas of current capability.
An “X” indicates a feature that was available in a vendor’s product during Q1 2015.
Cloud Platform Support Vendors (A – D)
Capability
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical
applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an
application, portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data “storytelling”
Adaptive
Insights
Birst
Dimensio
nal
Insight
X
X
X
X
X
Dundas
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
http://www.dresneradvisory.com
X
X
X
X
X
Copyright 2015 Dresner Advisory Services, LLC
39
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Mobile Platform Support Vendors (A – D)
Capability
Adaptive
Insights
Birst
Dimensio
nal
Insight
X
X
Dundas
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical
applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an
application, portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data ”storytelling”
X
X
X
X
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
40
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Traditional Platform Support Vendors (A – D)
Capability
Adaptive
Insights
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical
applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an
application, portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data “storytelling”
http://www.dresneradvisory.com
Birst
Dimensio
nal
Insight
X
X
X
X
X
Dundas
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copyright 2015 Dresner Advisory Services, LLC
41
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Cloud Platform Support Vendors (I – K)
Capability
IBM
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an application, portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data "story telling"
http://www.dresneradvisory.com
Infor
X
X
Informati
on
Builders
X
X
X
X
Klipfolio
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copyright 2015 Dresner Advisory Services, LLC
42
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Mobile Platform Support Vendors (I – K)
Capability
IBM
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an application, portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data "story telling"
http://www.dresneradvisory.com
X
X
Infor
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Informati
on
Builders
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Klipfolio
X
X
X
X
X
Copyright 2015 Dresner Advisory Services, LLC
43
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Traditional Platform Support Vendors (I – K)
Capability
IBM
Infor
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an application, portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data "story telling"
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
http://www.dresneradvisory.com
X
X
X
X
X
X
X
X
X
X
X
X
Informati
on
Builders
X
X
X
X
Klipfolio
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copyright 2015 Dresner Advisory Services, LLC
44
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Cloud Platform Support Vendors (L – M)
Capability
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical
applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an application,
portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data "story telling"
Logi
Analytics
X
X
X
X
X
X
X
X
X
X
X
X
X
Microsoft
X
X
X
X
X
X
X
X
X
X
X
http://www.dresneradvisory.com
X
X
X
X
X
X
X
X
X
X
X
X
X
X
MicroStrat
egy
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copyright 2015 Dresner Advisory Services, LLC
45
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Mobile Platform Support Vendors (L - M)
Capability
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical
applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an application,
portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data "story telling"
Logi
Analytics
X
X
X
X
X
X
X
X
X
X
X
X
X
Microsoft
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
MicroStrat
egy
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
46
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Traditional Platform Support Vendors (L - M)
Capability
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical
applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an application,
portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data ”story telling"
Logi
Analytics
X
X
X
X
X
X
X
X
X
X
X
X
X
Microsoft
X
X
X
X
X
X
X
X
X
X
X
http://www.dresneradvisory.com
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
MicroStrat
egy
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copyright 2015 Dresner Advisory Services, LLC
47
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Cloud Platform Support Vendors (O - Q)
Capability
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an application, portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data "story telling"
http://www.dresneradvisory.com
Oracle
Pentaho
Pyramid
X
X
X
X
X
X
X
X
Qlik
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copyright 2015 Dresner Advisory Services, LLC
48
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Mobile Platform Support Vendors (O - Q)
Capability
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an application, portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data "story telling"
http://www.dresneradvisory.com
Oracle
X
X
X
X
X
X
X
X
X
X
X
X
Pentaho
Pyramid
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Qlik
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copyright 2015 Dresner Advisory Services, LLC
49
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Traditional Platform Support Vendors (O - Q)
Capability
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an application, portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data "story telling"
http://www.dresneradvisory.com
Oracle
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Pentaho
Pyramid
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Qlik
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copyright 2015 Dresner Advisory Services, LLC
50
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Cloud Platform Support Vendors (R - S)
Capability
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an application, portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data "story telling"
http://www.dresneradvisory.com
RapidMiner
SAP
SAS
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
SiSense
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copyright 2015 Dresner Advisory Services, LLC
51
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Mobile Platform Support Vendors (R - S)
Capability
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an application, portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data "story telling"
http://www.dresneradvisory.com
RapidMiner
SAP
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
SAS
SiSense
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Traditional Platform Support Vendors (R - S)
Capability
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an application, portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data "story telling"
http://www.dresneradvisory.com
RapidMiner
X
X
X
X
X
X
X
X
X
X
X
SAP
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
SAS
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
SiSense
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copyright 2015 Dresner Advisory Services, LLC
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Cloud Platform Support Vendors (T - Y)
Capability
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an application, portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data "story telling"
http://www.dresneradvisory.com
Tableau
TIBCO
Yellowfin
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copyright 2015 Dresner Advisory Services, LLC
54
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Mobile Platform Support Vendors (T - Y)
Capability
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an application, portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data "story telling"
http://www.dresneradvisory.com
Tableau
TIBCO
Yellowfin
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copyright 2015 Dresner Advisory Services, LLC
55
2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Traditional Platform Support Vendors (T - Y)
Capability
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)
Custom CSS
Data mining and advanced algorithms
Data visualization
End user "self service"
In-memory support
Interactive analysis
Personalized dashboards
Pre-packaged vertical/functional analytical applications
Production reporting
Social media analysis (Social BI)
Text analytics
Data integration/data quality tools/ETL
Embedded BI (contained within an application, portal, etc.)
Search-based interface
Location intelligence/analytics
End user data "blending" or "mashups"
Data "story telling"
http://www.dresneradvisory.com
Tableau
TIBCO
Yellowfin
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Copyright 2015 Dresner Advisory Services, LLC
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Appendix - The 2015 Wisdom of Crowds® Business Intelligence Market
Survey Instrument
http://www.dresneradvisory.com
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
http://www.dresneradvisory.com
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
http://www.dresneradvisory.com
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
http://www.dresneradvisory.com
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
http://www.dresneradvisory.com
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
http://www.dresneradvisory.com
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
http://www.dresneradvisory.com
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2015 Small and Mid-Sized Enterprise Business Intelligence Market Study
Other Dresner Advisory Services Research Reports
-
Wisdom of Crowds “Flagship” Business Intelligence Market study
Advanced and Predictive Analytics
Business Intelligence Competency Center
Cloud Computing and Business Intelligence
Collaborative Computing and Business Intelligence
Embedded Business Intelligence
End User Data Preparation
Enterprise Planning
Internet of Things and Business Intelligence
Location Intelligence
Mobile Computing and Business Intelligence
Small and Mid-sized Enterprise Business Intelligence
http://www.dresneradvisory.com
Copyright 2015 Dresner Advisory Services, LLC
69