Brett Sheppard briefed author Cindi Howson in The Briefing Room to discuss Tableau’s data discovery tools.
Visual data discovery seems to be all the rage this year with new products and high-growth companies. What’s driving this interest – the pretty pictures or the self-service? And will this new category of tools finally take business intelligence (BI) mainstream or are we simply trading spreadsheet chaos for another kind of chaos?
There is still a fair amount of confusion about what is visual data discovery and what it is not, so I’ll start with a definition:
Visual data discovery tools speed the time to insight through the use of visualizations, best practices in visual perception, and easy exploration. Such tools support business agility and self-service BI through a variety of innovations that may include in-memory processing and mashing of multiple data sources.
Some befuddled BI teams though are shrugging their shoulders and asking, “Isn’t that what ad hoc business queries were supposed to do?” Well, yes, to a degree. Two of the biggest differences in business query tools and visual data discovery tools are the use of graphs and the degree of user autonomy. In a business query tool, a user can certainly add a bar chart to a dense page of numbers. But the chart is an after-thought. In fact, according to a TDWI survey last year, users spend two-thirds of their time analyzing data in tabular versus chart form. This may be appropriate when you need a precise number (How many widgets do we have on hand?), but not when you are trying to identify patterns, trends, and anomalies. With visual data discovery tools, the query and visualization process are one in the same. Drag a time period onto the page and up pops a trend line. Add a product category, and perhaps that trend line is now automatically converted to a trellis or small multiple chart. Research has shown that when data is represented graphically, we use less cognitive resources to make a decision and retain information better. So these graphs are more than just pretty or engaging; it’s about speeding the time to insight.
The other big distinction with visual data discovery tools from business query tools is the degree of user autonomy. Business query tools generally require a metadata layer that IT will often design and build. This metadata layer provides a layer of abstraction from the physical database schema with potentially hundreds of tables. With a visual data discovery tool, business users are often working with a subset of data, either a flat file or spreadsheet, so IT is not a bottleneck. If a real-time query is involved, the visual data discovery tool may automatically model a metadata layer, giving its best guess at what’s a metric and what’s a dimension, again with little to no IT support. Somebody would have to write the SQL for the initial query and define the joins, but once extracted, the data is often loaded into an in-memory engine.
3. Twitter Tag: #briefr
Reveal the essential characteristics of enterprise
software, good and bad
Provide a forum for detailed analysis of today’s
innovative technologies
Give vendors a chance to explain their product to
savvy analysts
Allow audience members to pose serious questions...
and get answers!
Mission
Tuesday, August 7, 2012
5. Twitter Tag: #briefr
Analytics has always been about discovering
insights that lead to better business decisions.
Organizations can be challenged by the complexity
of information management as they try to leverage
analytics against disparate sources.
A growing number of vendors are offering robust
visualization tools to help customers quickly and
easily perform analytics against data from any
source, from any device.
Analytics
Tuesday, August 7, 2012
6. Twitter Tag: #briefr
Analyst: Cindi Howson
Cindi Howson is the founder of BI Scorecard, a resource
for in-depth BI tool evaluations based on exclusive
hands-on testing. She is the author of several BI books
including Successful Business Intelligence: Secrets to
Making BI a Killer App, a TDWI faculty member, and a
frequent contributor to Information Week. As a
consultant, she advises clients on BI strategies and tool
selections.
Prior to founding BI Scorecard, Howson was a manager
at Deloitte & Touche and a BI standards leader for a
Fortune 500 company.
She has an MBA from Rice University.
Tuesday, August 7, 2012
7. Twitter Tag: #briefr
Tableau builds software for data visualization and
rapid-fire business intelligence. Their mission is to
help people see and understand data.
Tableau offers a wide variety of data representation
possibilites.
Its BI platform fits both power users and casual BI
users.
Tableau was recently ranked by Forrester as the #1
Advanced Data Visualization vendor.
Tableau
Tuesday, August 7, 2012
8. Twitter Tag: #briefr
Brett Sheppard is the Senior Product
Marketing Manager at Tableau Software
where he helps people and organizations see,
understand and communicate data. Previous
roles include Gartner senior analyst,
financial editor at Investor Relations Corp.,
and product or solution marketing roles at
Greenplum (acquired by EMC), HP business
intelligence solutions, Nortel Networks and
Symantec.
An early starter, Brett worked in product
marketing at data storage startup Maynard
Electronics (acquired by Symantec/Archive
Corp.) and in college as a data analyst at the
U.S. Department of Defense as an employee
of CASDE Corp./DDL OMNI Engineering.
Brett Sheppard
Tuesday, August 7, 2012
12. Tableau Desktop
For Anyone
• Explore and visualize data
• Self-service analytics for everyone
• Blazing speed against massive data
Tuesday, August 7, 2012
13. Tableau Server
For Organizations
• An easy business intelligence system
• Web dashboards and applications
• Secure information management
• Enterprise scalability
Tuesday, August 7, 2012
21. 21
Analytic Democracy:
Spreading the Wealth of Insight
Cindi Howson
Founder, BI Scorecard
Contact: cindihowson@biscorecard.com
Twitter: BIScorecard
Tuesday, August 7, 2012
22. Visual Data Discovery Defined
22
Visual Data Discovery tools speed the time to
insight through the use of visualizations, best
practices in visual perception, and easy
exploration. Such tools support business
agility and self-service BI through a variety
of innovations that may include in-memory
processing and mashing of multiple data
sources.
Tuesday, August 7, 2012
23. Business Users Are Excited About BI
23
Visual Data Discovery Drivers
Tuesday, August 7, 2012
24. Business Users Are Excited About BI
23
Visual Data Discovery Drivers
Visual
Appeal
Tuesday, August 7, 2012
25. Business Users Are Excited About BI
23
Visual Data Discovery Drivers
Visual
Appeal
Ease of
Use
Tuesday, August 7, 2012
26. Business Users Are Excited About BI
23
Visual Data Discovery Drivers
Visual
Appeal
Ease of
Use
Freedom
from IT
Tuesday, August 7, 2012
27. Business Users Are Excited About BI
23
Visual Data Discovery Drivers
Visual
Appeal
Ease of
Use
Freedom
from IT
Social
data
Tuesday, August 7, 2012
29. Visual Data Discovery – Hidden Insights
• What are sales by
customer?
• What are sales by
customer this year versus
last year?
Tuesday, August 7, 2012
30. Visual Data Discovery – Hidden Insights
• What are sales by
customer?
• What are sales by
customer this year versus
last year?
Tuesday, August 7, 2012
31. Visual Data Discovery – Hidden Insights
• What are sales by
customer?
• What are sales by
customer this year versus
last year?
• What are characteristics
of customers with higher
sales?
• What are characteristics
of customers who have
churned?
Tuesday, August 7, 2012
32. 25
Visualization vs. Visual Data Discovery
Visualization
• Common charts types
– Bar, line, pie
• Sometimes additional chart
types such as maps, gauge
• Query, get tabular result,
then visualize
• Data often from DW or
OLAP cube
• Interactivity not guaranteed
Visual Data Discovery
• Less common chart types
– Small multiples, waterfall, network, heat
or tree map, spark line, tag cloud
• Best practices in visualization
– No pies, smart use of color
• Single-step query and visualize
• Highly interactive
• Data mashed from DW, marts,
spreadsheets
• May be “personal” analytic tool
• Rapid prototyping and
deployment
Tuesday, August 7, 2012
35. Self-Service BI Continuum
Free-form
SQL &
Ad-hoc
query,
broad
Explorer &
navigate
Tweak a
report
Reporting
application or
visual data
discovery
Tuesday, August 7, 2012
36. Self-Service BI Continuum
Free-form
SQL &
Ad-hoc
query,
broad
Explorer &
navigate
Tweak a
report
Reporting
application or
visual data
discovery
Casual
User
Tuesday, August 7, 2012
37. Self-Service BI Continuum
Free-form
SQL &
Ad-hoc
query,
broad
Explorer &
navigate
Tweak a
report
Reporting
application or
visual data
discovery
Casual
User
Expert
Tuesday, August 7, 2012
38. Self-Service BI Trade-Off Continuum
IT Involvement User Autonomy
AnalyticComplexity
•Size of bubble=user
flexibility
•Darker color =skills
required to author
Tuesday, August 7, 2012
39. Self-Service BI Trade-Off Continuum
IT Involvement User Autonomy
AnalyticComplexity
Fixed
Reports
•Size of bubble=user
flexibility
•Darker color =skills
required to author
Tuesday, August 7, 2012
40. Self-Service BI Trade-Off Continuum
IT Involvement User Autonomy
AnalyticComplexity
Fixed
Reports
Spreadsheets
•Size of bubble=user
flexibility
•Darker color =skills
required to author
Tuesday, August 7, 2012
41. Self-Service BI Trade-Off Continuum
IT Involvement User Autonomy
AnalyticComplexity
Fixed
Reports
Spreadsheets
Business
Query
•Size of bubble=user
flexibility
•Darker color =skills
required to author
Tuesday, August 7, 2012
42. Self-Service BI Trade-Off Continuum
IT Involvement User Autonomy
AnalyticComplexity
Fixed
Reports
Spreadsheets
Business
Query
Visual
Discovery
•Size of bubble=user
flexibility
•Darker color =skills
required to author
Tuesday, August 7, 2012