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Overview
A PICTURE IS WORTH A THOUSAND WORDS—or in the case of business
intelligence (BI), it is worth a thousand or more data points. After all, human
beings are visual creatures. This is how we perceive and make sense of our
surroundings. So doesn’t it make sense for us to use visually oriented
techniques to perceive and make sense of our business world as well?
Visual discovery,
because of its
improved ease of
use and
consumption,
means it is an
ideal technology
for business users
who want to
serve themselves.
But creating a pretty picture is only part of the batt Visual discovery must
also enable the business user to discover new things and interact with the data.
Visual discovery tools allow the business user to get a quick understanding of a
business situation and then zoom in, filter out and obtain details on demand—
basically to allow the data to tell the businessperson its story. It is a dynamic
form of a narrative or persuasio—all occurring with minimal IT intervention
What is Visual Discovery?
THERE SEEMS TO BE A LOT OF CONFUSION regarding traditional BI andvisual
discovery. Here are two standard definitions for these different styles of BI
Traditional BI toolsare predominantly controlled, driven and
implemented by corporate IT. The outputs tend to be mostly static
dashboards, tabular reports, or simple OLAP analyses. The users have
limited interaction, mostly in the form of drilling down through the levels
of summarized or aggregated data to the detailed data. Changes and
enhancements to the environment generally require IT intervention,
which is why many people refer to this form as “managed reporting.
Visual discovery tools turn the data into visual perceptions that the
users can manipulate and interact with. Corporate IT may still be
involved, but a large part of the creation of different visualizatis rests
in the hands of the business user.
Visual discovery, because of its improved ease of use and consumption, means
it is an ideal technology for business users who want to serve themselves.
These users want the improved level of autonomy that self-service BI offers
them, and surveys have shown that this is a major driver for many
implementations of these technologies
Visualization techniques vary and include simple actions like mouseover fo
displaying tips, metadata, or available functions when e cursor rests over an
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object; auto-suggesting for chart types that fit the data better; lassoing o
selecting specific data values in a chart by circling them with a cursor; an
animations that show how the data values have changed over time. For mor
on visualization techniques as well as information on evaluation criteria, s
“Visual Discovery Tools: Market Segmentationand Product Positionin” by
Wayne Eckerson.
Finally, many visual discovery tools have some kind of proprietary data
structure for storing and modeling the data. Many times, but not always, this is
an in-memory and/or columnar database.
The benefits from
deploying visual
discovery
implementations
are varied and
broad.
Market Trends and Adoption Rat
VISUAL DISCOVERY HAS HAD A CONSIDERABLE IMPACT on overall BI solution
sales. Many companies today consider its capabilities as a mandatory part of
their BI environment, often replacing the popular but somewhat limited Excel
spreadsheet. It seems that once visual discovery lands on a business user’s
desk, others take notice and visual discovery begins to spread rapidly
throughout the company. Also, BI vendors have found that attractiv
dashboards using visual discovery capabilities make for easier sells to their
prospects.
When should visual discovery techniques be used? It turns out that these
techniques are very useful in performing various analytical acvities like tiseries and performance analyses. It is also useful in analyzing and monitoring
predefined metrics and conducting wha-if scenarios, detecting outliers that
may indicate a new trend, and uncovering new relationships between events,
customers, products, campaigns, etc.
The adoption rate for visual discovery tools is quite good. Our survey shows
that almost 50% of the respondents have either fully deployed or partially
deployed these tools in their organizations. This increase indicates the
compelling need of business users to have better and faster ways to gain insight
into unfolding business scenarios.
Business Benefits
THE BENEFITS FROM DEPLOYING VISUAL DISCOVERY IMPLEMENTATIONS are
varied and broad. Better insight, faster time to discery, and more analysis
with less data manipulation are some. The most popular benefits are
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Comprehension: Visualizations of data communicate complex data
relationships, such as patterns, trends, outliers, etc., far faster than
series of numbers in a table, spreadsheet or a text-based report. It
greatly improves the time to insight so mandatory in today’s competiti
environment. Basically, visual discovery is very effective at providing
access to the right information at the right tim
As with all new
implementations,
visual discovery
projects have
their own set of
challenges.
Interaction Visual discovery allows the businessperson to determine
what to manipulate, filter, select, and drill into very quickly. The selfservice environment fostered by visual discovery means business users
can address unanticipated data needs in a far more timely manne The
person’s productivity is greatly enhanced and their knowledge is
significantly increased through visual discovery.
Discovery of unknown relationships Visual presentations of data quickly
uncover previously unknown patterns, trends and other relationship
between data and events. This allows analysts to spend more time
actually analyzing and thinking about why these relationshipsare
occurring rather than grinding through endless spreadsheets, columns of
numbers, and tabular reports.
Adoption of BI assets Because visual discovery speeds time to insight, it
has also increased the number of business users utilizing BI assets
throughout the enterprise (see adoption rates above). The resultin
effect is that companies are becoming much more data-driven and
analytical in terms of their decision making
Better leverage of IT resources Because of the business user’s
propensity for creating a sel-service BI environment with visual
discovery tools, IT resources are freed up to pursue more strategic
activities that have greater business value to the enterprise. Thes
include developing new applications, expanding data in the data
warehouse, improving data quality processing, and incorporating new
technologies to improve performance. IT becomes more of a partner
than a roadblock to business users wanting BI asset—which means that
IT and the businesspeople have an improved collaborative reationship
Challenges
AS WITH ALL NEW IMPLEMENTATIONS, visual discovery projects have
their own set of challenges or pitfalls that can derail a successful
initiative. Here are a few of the more common challenge
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Bias in visualizations Visualization shold be designed to be devoid of
bias—it should be based on what the data actually says, not on what the
user wants it to say. You can create a misleading graph easily just by
presenting a number that is 3 times bigger than another one in a 3
format. The 3D format makes the number appear to be nine times
bigger. Omitting outliers, using capped values, or arbitrary tempora
ranges can be fraught with peril in that the outliers or out-of-range
values may be early warning indicators of new and perhaps devastatng
trends or patterns
Visual discovery is
meant to breathe
life into data; it
enhances a
person’s ability to
improve his or her
business insight.
Bad design: The visual design is not a trivial matter and much literature
has been written covering theproper design of visual graphics.
Something to keep mind is that you can bring balance to visual designs
by simply presenting the same data in alternative representation
labeling everything to avoid ambiguity, and using standardized
measurements and units. And make sure you develop a variety of visual
graphics—the much-maligned pie chart has many, far more interesting
relatives Each user has his or her own way of viewing data so make sure
you match the right type of visualization to the business user an the
problem at hand. A good practice is to create a prototype and get
feedback on the design.
Visual overload: Businesspeople are bombarded daily with images from
a multitude of different sources. Constant exposure to overly
complicated, highly dimensionalized visualizations can actually cause the
businessperson to become “numb” to what he or she is seeing. A
recommendation is to focus on having the visualization explain the data
not decorate it. Secondly, to turn passive viewing into a dynamic and
partcipatory experience, businesspeople must be able to interact with
the information. They need to be able to view, touch, interpret and
identify trends or patterns. The users retain the information better
use fewer resources to make a decision when they can interact and
discover. Successful visual discovery projects will empower their users
without overwhelming them.
It is important to remember that visual discovery is meant to breathe life into
data; it enhances a person’s ability to comprehend complex relationships
quickly and to improve his or her business insight. Visual discovery has a story
to tell. If you are unsure how to design your visual discovery environment, hire
an expert in design. They can guide you through the process.
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Perception
A PERCEPTION IN THE MARKETPLACE is that business departments, frustrated
with their IT departments, purchase visual discovery tools predominantly. This
may have been true 5 years ago; but more and more today, we are seeing
enterprise-class solutions being rolle out by IT. Of course, these
implementations are still quite different from traditional-driven BI
environments. They are far more self-service oriented and give the business
users much more freedom and access to their own data sources as well as ITcreated data warehouses and marts.
The bottom line is
that visual
discovery tools
are
complementary to
BI tools, not
alternatives to
them.
A second perception is that visual discovery will replace traditional BI. It i
important to acknowledge that traditonal BI still has its role and is the
appropriate way to communicate certain types of data. For example, rankings
(top 10, bottom 10%, etc.) of sales, customers, salesperson performance, etc.
are easily and best displayed in a text-based format. Traditionl BI technology is
suitable for situations where the exact number or value of a metric or
measurement is required or where there is a need to provide routine
information quickly and efficiently
Third, many people believe that visual discovery tools are implemented by
individual departments or business units in their attempts to create a selservice BI environment. Our survey dispels this perception. When asked which
best describes the scale and scope of their visual discovery deployments, the
highest respondent answer (39%) was for the enterprise. Respondents selected
business unit 29% and departmental 25% of the time. It seems that
organizations want visual discovery tools to reside in a centralized fashion
much like their traditional BI environments. Tis is further reinforced by our
respondents’ response to the question, “Which data sources are accessed by
your visual discovery tools?” An overwhelming 72% answered the enterprise
data warehouse.
Finally, there is a perception that visual discovery tool belong solely to the
business users and IT either does not have a role or does not need to know
about them. Neither of these is correct. Corporate IT has a significant role in
monitoring this environment, ensuring that security and privacy policies are in
place, and expanding the sources of data and making them accessible to the
business community. The savvy IT department will embrace these technologies
and truly become the business partner they should be.
The bottom line is that visual discovery tools are complementary to BI tools,
not alternatives to them. They enhance the overall user experience for certain
Visual Discovery: Perceptions and Market Trends
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types of BI analyses, thus improving the overall adoption of BI assets in most
organizations. They improve the adoption of BI assets throughout th
organization, thus moving it to a more analytically savvy enterpris
Survey Results
Visual discovery
tools have built
quite a following
in the past
decade, and it is
safe to say that
they are
mainstream BI
tools.
THE REMAINDER OF THIS REPORT PROVIDES MARKET PERSPECTIVES on visual
discovery tools. The following charts are based on a survey of 192 BI
professionals conducted in April 2013 by the BI Leadership Forum, a LinkedIn
group for BI directors and their teams. Two-thirds (66%) of the respondents are
BI professionals, 19% are BI consultants, 8% are business users or sponsors, and
7% are “other”. (We discarded responses from vendors and academics.) About
half (46%) come from large companies with more than $1 billion in revenue,
while another third (33%) are medium-size companies with between $100
million and $1 billion in revenue, and 21% are small companies with less than
$100 million in revenue. Slightly more than half (51%) rated their BI maturity as
“intermediate” while 25% rated their maturity as “advanced” and 23% said
they were “beginners.”
Adoption Rat
VISUAL DISCOVERY TOOLS HAVE BUILT QUITE A FOLLOWING in the past
decade, and it is safe to say that they are mainstream BI tools. Almost half
(49%) of respondents have deployed visual discovery tools (fully or partially),
while another 18% are under development. One-third (34%) have yet to take
the leap, saying that they either have “no plans” or have a project “under
consideration.” (See Figure 1.
Figure 1: What is the status of visual discovery tools at your organization
No plans
10%
Under consideration
Under development
24%
18%
Partially deployed
Fully deployed
30%
19%
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Scope
MOST VISUAL DISCOVERY VENDORS SELL THEIR PRODUCTS to business unit
and department heads, not IT. As such, the products have a reputation as being
departmental BI tools. However, our data shows that 39% of companies have
deployed visual discovery tools on an enterprise basis. This could mean that
either they’ve standardized on a visual discovery toolset or that visual discovery
tools have proliferated independently throughout the organization. More than
half (54%) said that the scope of their deployments is confined either to
business units or departments. (See Figure 2.)
Our data shows
that 39% of
companies have
deployed visual
discovery tools on
an enterprise basis.
Figure 2: Which best describes the scale and scope of your visual discovery
deployment?
Not deployed
3%
Departmental
25%
Business unit
29%
Enterprise
Other
39%
5%
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Deployments
WHEN ASKED HOW MANY SEPARATE INSTANCES of visual discovery tools exist
in their organization, respondents were split into two camps. Almost half (49%)
said they only had one or two instances, which suggests either an enterprise
deployment or a limited departmental deployment. Another 28% said they had
more than 10 separate instances, with 12% citing more than 21 instances.
These latter results reflect the “land and expand” strategy of visual discovery
vendors in which a single department purchases a tool and, when word gets
out, other departments jump on board with their own purchase and
implementation.
“Enterprise
deployment”
means that the
tools have
proliferated
independently to
the point that they
have become a
default enterprise
standard.
When we drilled into the respondents with enterprise deployments, the results
were not dissimilar. Fift-one percent of enterprise customers said they had
one or two instances (versus 49%) and 31% said they had 10 or more instances
(versus 28%) with 20% citing more than 21 instances.So, it appears that
“enterprise deployment” means that the tools have proliferated independently
to the point that they have become a default enterprise standard.
Figure 3: How many separate instances of visual discovery tools exist in your
organization
0
2%
1 to 2
49%
3
4 to 5
14%
7%
6 to 10
11 to 20
21+
10%
6%
12%
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Integration
THE MAJORITY OF DEPARTMENTS AND BUSINESS UNITS generally deploy
visual discovery tools independently and don’t do much to integrate them.
Almost two-thirds (64%) said that some or all of their instances of visual
discovery tools are not linked. However, the remainder (36%) said either most
or all their instances share data and definitions. Organizations with enterpris
deployments have done a much better job of integrating multiple instances
visual discovery tools.
Organizations with
enterprise
deployments have
done a much better
job of integrating
multiple instances
of visual discovery
tools.
More than half (53%) said that either most or all of their instances are
integrated (versus 36% for all respondents.) As we’ll see in the next question,
most of this integration comes from querying integrted data in a data
warehouse rather than source systems directly.
Figure 4: To what degree has your organization linked separate instances of
visual discovery tools?
None – Instances are not linked; each is
an island of information
19%
Some – Some instances share data and
definitions, but most don't
Most – Most instances share data and
definitions, but not all
All – All instances share data and
definitions
Visual Discovery: Perceptions and Market Trends
45%
15%
20%
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Data Sources
THE IDEAL WAY TO DEPLOY A VISUAL DISCOVERY TOOL to avoid creatng
departmental data silos is to point the tool at the enterprise data warehouse.
Comfortingly, almost tw-thirds (72%) of organizations take this appoach. But
they also populate the visual discovery tool with data from many other sources,
especially local files (58%), which is a legitimate way to enhance corporate
data. Less comforting is that more than half of respondents (52%) said they use
visual discovery tools to query enterprise applications, which is a surefire recipe
for creating stovepipe analycal systems.
The ideal way to
deploy a visual
discovery tool to
avoid creating
departmental data
silos is to point the
tool at the
enterprise data
warehouse.
Figure 5: What data sources does your visual discovery tool access?
Enterprise data warehouse
72%
Local files (e.g., Excel)
58%
Enterprise applications (e.g., ERP)
52%
Departmental data mart
49%
Departmental applications (ERP/CRM)
44%
External data
31%
Web services
12%
Hadoop/NoSQL
Other
10%
5%
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Standardization
A MAJORITY OF COMPANIES HAVE ESTABLISHED STANDARDS governing the
use of visual discovery tools, but those standards vary widely. (About one-third
(35%) have no corporate policies or standards for visual discovery tools.) More
than one-third (38%) have standardized on the tools for creating enterprise
dashboards, while slightly less than one-third (32%) standardize on the tools for
business analysts. Another 30% also standardize on the tools for creating
departmental dashboards. Only 14% prohibit departments from purchasing the
tools. (Good luck with that!)
A majority of
companies have
established
standards
governing the use
of visual discovery
tools.
Figure 6: What is the corporate policy regarding the use of visual discovery
tools?
Standardize on the tools for creating
enterprise dashboards
38%
No corporate policy needed
35%
Standardize on the tools for business
analysts
32%
Standardize on the tools for creating
departmental dashboards
30%
Prohibit departments from purchasing
the tools
Require the departments to point the
tools at the EDW
14%
13%
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Users
VISUAL DISCOVERY TOOLS SERVE MULTIPLE AUDIENCES. Although the desktop
tools are designed for power users to analyze data, they can also be used to
author Web-based dashboards that can be used by casual users. Accordingly,
47% of companies say that both casual and power users are the primary users
of visual discovery tools. However, 44% say their tools are used primarily by
power users only. Not surprisingly, in companies that have standardized on
visual discovery tools for business analysts (see Figure 6 above), a larger
percentage say their primary users are power users (54% versus 44% for all
companies).
Forty-seven percent
of companies say
that both casual
and power users
are the primary
users of visual
discovery tools.
Figure 7: Who are the primary users of your visual discovery tools?
Casual users
9%
Power users
Both equally
Visual Discovery: Perceptions and Market Trends
44%
47%
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15. BENCHMARK REPORT
Features
WHEN IT COMES TO FEATURES, POWER USERS ARE MORE ACTIVE USERS of
visual discovery tools. A majority use the tools to connect to a single or multiple
data sources and analyze predefined metrics. More than one-third use the tools
to monitor predefined metrics (37%), conduct what-if analyses (37%), and
author and publish dashboards (33%).
The top feature used by casual users is to “monitor predefined metrics” (37%),
followed by connecting to a single data source (24%)
The top feature
used by casual
users is to “monitor
predefined
metrics,” followed
by connecting to a
single data source.
Figure 8: To what degree do your users use the following functions in the
visual discovery tool? (Percentages based on responses equal to “high”)
Power User
Casual User
Connect to, explore, and analyze a single
data source
Connect to, explore, and analyze multiple
data source
55%
15%
Analyze predefined metrics
37%
37%
Conduct what-if analysis
Enter or update data
Transform, clean, and/or combine data
Apply data mining algorithms (e.g.,
regressions)
49%
22%
Monitor predefined metrics
Author and publish dashboards
59%
24%
37%
11%
33%
7%
4%
4%
4%
Visual Discovery: Perceptions and Market Trends
21%
21%
20%
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Satisfactio
A MAJORITY OF BUSINESS USERS RATE VISUAL DISCOVERY TOOLS either
“better” or “much better” than their existing BI tools. The most enthusias
users are business users (81%), followed by department heads (68%) and
executives (67%). Least enthsiastic are IT managers (45%), which is not
surprising since most implementations are not initiated or cleared by them
Nonetheless, 45% is still a large percentage. And 49% of IT managers are
neutral about the tools, leaving only 5% who rate them less favorably than
existing BI tools
A majority of
business users rate
visual discovery
tools either
“better” or “much
better” than their
existing BI tools
Figure 9: The value of visual discovery tools is better or much better than othe
BI tools in use at our organization
Business users
81%
Business department heads
68%
Executives
67%
IT department heads
Visual Discovery: Perceptions and Market Trends
45%
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17. BENCHMARK REPORT
Purchasing Drivers
THE PRIMARY REASONS FOR PURCHASING a visual discovery tool are “better
visualization” (78%), “easier to use” (77%), and “sel-service analysis” (66%).
This was followed by “fast-changing business requirements” (53%), “self-service
authoring” (51%), “quicker to deploy” (51%) and “faster queries” (45%).
Figure 10: What drove the decision to purchase a visual discovery tool?
Better visualization
The primary
reasons for
purchasing a visual
discovery tool are
“better
visualization,”
“easier to use” and
“self-service
analysis.”
78%
Easier to use
77%
Self-service analysis
66%
Fast-changing business requirements
53%
Self-service authoring
51%
Quicker to deploy
51%
Faster queries
45%
Faster data integration
More affordable
33%
25%
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Challenges
NO TECHNOLOGY IS WITHOUT ITS CHALLENGES, and that holds true for visual
discovery tools. About one-third of respondents experience significant difficulty
with the following four issues:
No technology is
without its
challenges, and
that holds true for
visual discovery
tools.
1. Sourcing data from complex ERP/CRM systems (complexity)
2. Maintaining data consistency across environments (consistency)
3. Getting executives to fund the installation or expansion of the soft
(funding)
4. Identifying and fixing ata quality issues (data quality)
5. Maintaining performance as number of users and volume of data
increases (scalability).
They have slightly fewer issues with meeting performance commitments and
integrating the tools with other environments, such as dataase management
systems.
Figure 11: “To what degree have you experienced the following challenges
with visual discovery tools?” (Percentages based on responses equal to
“high.”)
Complexity
33%
Consistency
33%
Funding
32%
Data quality
31%
Scalability
27%
Performance
21%
Integration
21%
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Future Plans
DESPITE THE CHALLENGES above, companies are bullish on visual discovery
tools—in fact, very bullish. The vast majority (84%) plan to expand their
deployments, while just 2% will decrease the scope of their deployments. This
is the best reference for the value and quality of visual discovery tools as any
since it involves spending hard-earned dollars on a technology.
Figure 12: What are your future plans for deploying visual discovery tools?
Despite the
challenges,
companies are
bullish on visual
discovery tools.
Expand deployment
84%
Maintain, but not expand
Decrease deployment
13%
2%
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Why Not?
SO FAR, OUR DATA HAS FOCUSED on those users who have deployed visual
discovery tools. It’s clear that they are very pleased with the tools. However,
one-third of survey respondents have yet to deploy a visual discovery tool.
Among this group, there are various reasons for holding off a purchase. The
primary reason is lack of budget to buy the tools (35%), followed by the fact
that they are adequately served by their existing BI tools (29%), the tools are
not part of the corporate standard (27%) and, perhaps most significant of all,
there is a fear that the tools will proliferate spreadmarts (25%).
One-third of survey
respondents have
yet to deploy a
visual discovery
tool.
Figure 13: What prevents you from deploying visual discovery tools?
Our budget is tapped out
35%
We already have suitable BI tools
29%
Not a corporate standard
27%
Fear of proliferating spreadmarts
25%
Don't know enough about visual discovery tools
19%
Performance and scalability issues
18%
Other
18%
Not enough value for the price
Visual Discovery: Perceptions and Market Trends
12%
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Recommendations
OUR SURVEY RESPONDENTS OFFERED LOTS OF ADVICE about how to get the
most out of visual discovery tools while avoiding its pitfalls
Complementary. Many said visual discovery tools complement their BI
standard, not replace it. “Use the right tool for the right situation,” said
one. Another said BI vendors could help here by allowing visual discovery
tools to query enterprise BI tools.
Most respondents
recommended
getting th
corporate BI team
involved prior to
deploying visual
discovery tools to
avoid creating
problems down the
road.
Metadata. Most respondents were adamant that visual discovery tools
do not address business metadata but, in fact, often undermine it. Thus,
they said it is imperative for the BI team to build the data layer (i.e.,
consistent definitions) that visual discovery tools can leverage. One said,
“I closed three instances last year because the business didn’t have
control over data quality or MDM. Nice tool but utterly useless if the
underlying data isn’t under control.”
IT Involvement. Most recommended getting the corporate BI tea
involved prior to deploying visual discovery tools to avoid creating
problems down the road. Many respondents worried about proliferating
spreadmarts, which they would eventually be asked to manage on an
enterprise basis despite data quality, scalability and performance
limitations. “These tools are creating a lot of l-value work for the BI
team” said one. Another said, “The tools are powerful but need to be
governed.”
Training. Although visual discovery tools support self-service, most
respondents insisted that users require lots of training to become
proficient users. In fact, one who uses the tool for discovery said, “Few
users have the aptitude and desire to explore data and tease out those
nuggets of gold.” Another who uses the tool for dashboard development
said, “These tools require highly skilled people to build solutions.”
Target. Some respondents also said to pick target applications for visual
discovery carefully. One said, “Start small with a high value data set that
is not currently being leveraged.” Another said, “Be specific about what
the tool delivers and deploy it only for that.” Some said the tools are
great for prototyping dashboards prior to enterprise development.
Another said that unless you have a “defined deployment model” you
are likely to be swamped with individual requests later on.
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Summary
VISUAL DISCOVERY TOOLS ARE POPULAR TODAY. Once they enter an
organization, they spread quickly. Business users love the tools because they
are highly visual, interactive, analytical and affordable. Moreover, they can b
used to create departmental dashboards, so they serve both power and casual
users. Organizations get a lot of bang out of every dollar they spend on visual
discovery tools.
To gain the full
benefit of visual
discovery tools,
organizations must
ensure that tool
users don’t
independently
source data that
already exists in the
corporate data
warehouse.
But visual discovery tools are not a panacea for every BI ill, despite what
vendors claim. They are the newest low-cost, analytical tool that power users
can use to create data silos and spreadmarts. To gain the full benefit of visual
discovery tools, organizations must ensure that tool users don’t independently
source data that already exists in the corporate data warehouse. IT needs to
get involved to ensure the consistency and quality of data. Finally, despite their
self-service moniker, visual discovery tools are not easy to use as authoring
tools. Some, in fact, require a great deal of data and programmatic skills.
Visual Discovery: Perceptions and Market Trends
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