2. What is the status of visual discovery
tools in your organization?
10%
24%
18%
30%
19%
No plans
Under consideration
Under development
Partially deployed
Fully deployed
3. Which best describes the scale and scope
of your visual discovery deployments?
3%
25%
29%
39%
5%
Not deployed
Departmental
Business unit
Enterprise
Other
4. How many separate instances of visual
discovery tools exist in your organization?
2%
49%
14%
7%
10%
6%
12%
0
1 to 2
3
4 to 5
6 to 10
11 to 20
21+
5. To what degree has your organization linked
separate instances of visual discovery tools?
19%
45%
15%
20%
None - Instances are not linked; each
are islands of information
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
instances
6. Which data sources are accessed by
your visual discovery tools?
72%
58%
52%
49%
44%
31%
12%
10%
5%
Enterprise data warehouse
Local files (e.g. Excel)
Enterprise applications (e.g. ERP)
Departmental data mart
Departmental applications…
External data
Web services
Hadoop/NoSQL
Other
7. On average, how many sources of data do your visual
discovery tools display within a single application?
54%
22%
14%
2%
4%
5%
1 to 2
3
4 to 5
6 to 10
11 to 20
21+
8. What is the corporate policy regarding
the use of visual discovery tools?
38%
35%
32%
30%
14%
13%
Standardize on the tools for
creating enterprise dashboards
No corporate policy needed
Standardize on the tools for
business analysts
Standardize on the tools for
creating departmental dashboards
Prohibit departments from
purchasing the tools
Require the departments to point
the tools at the EDW
9. Which vendors supply you with visual
discovery tools?
53%
35%
30%
27%
20%
19%
17%
12%
9%
3%
2%
2%
1%
1%
Tableau
Microsoft
QlikTech
SAP Business Objects
IBM Cognos
Microstrategy
Other
SAS Institute
Tibco Spotfire
Information Builders
SiSense
Actuate
Advizor
Alteryx
10. Who are the primary users of your
visual discovery tools?
9%
44%
47%
Casual users
Power users
Both equally
11. To what degree do casual users use the following
functions in the visual discovery tool? (Only “high”
responses displayed)
37%
24%
22%
15%
11%
7%
4%
4%
4%
Monitor predefined metrics
Connect to, explore, and analyze a single data source
Analyze predefined metrics
Connect to, explore, and analyze multiple data source
Conduct what-if analysis
Author and publish dashboards
Enter or update data
Transform, clean, and/or combine data
Apply data mining algorithms (e.g. regressions)
12. To what degree do power users use the following
functions in the visual discovery tool? (Only “high”
responses displayed)
59%
55%
49%
37%
37%
33%
21%
21%
20%
Connect to, explore, and analyze a single data source
Connect to, explore, and analyze multiple data source
Analyze predefined metrics
Monitor predefined metrics
Conduct what-if analysis
Author and publish dashboards
Enter or update data
Transform, clean, and/or combine data
Apply data mining algorithms (e.g. regressions)
13. How do each of the following groups rate the value of
visual discovery tools compared to other BI tools in
use at your organization?
38%
43%
18%
28%
40%
31%
13%
32%
49%
24%
43%
31%
Much better
Better
Neutral
Business users
Business department
heads
IT department heads
Executives
14. Which BI tools has your organization
officially standardized on?
87%
70%
56%
45%
31%
21%
Reporting/dashboard tool
Ad query/analysis tool
Visual discovery tool
Multidimensional OLAP tool
Real-time analytics/dashboard tool
Data mining tool
15. To what degree did the following drive the
decision to implement visual discovery tools?
78%
77%
66%
53%
51%
51%
45%
33%
25%
Better visualization
Easier to use
Self-service analysis
Fast-changing business requirements
Self-service authoring
Quicker to deploy
Faster queries
Faster data integration
More affordable
16. To what degree has your organization
experienced the following challenges with
visual discovery tools?
33%
33%
32%
31%
27%
21%
21%
Complexity - Sourcing data from complex ERP/CRM applications
Consistency - Maintaining data consistency across environments
Funding - Getting executives to expand to fund the installation
or expansion of the software
Data quality - Idetnifying and fixing data quality errors
Scalability - Maintaining performance as numbers of users and
volume of data increases
Performance - Meeting SLAs for response times
Integration - Integrating the tools with other information
environments
17. What are the future plans for the
deployment of visual discovery tools?
84%
13%
2%
Expand deployment
Maintain, but not expand
Decrease deployment
18. What prevents you from deploying
visual discovery tools?
35%
29%
27%
25%
19%
18%
18%
12%
Our budget is tapped out
We already have suitable BI tools
Not a corporate standard
Fear of proliferating spreadmarts
Don't know enough about visual discovery tools
Performance and scalability issues
Other
Not enough value for the price
