Great data strategies focus on delivery. The presentation will discuss: - The importance of how data is delivered to driving user adoption of data-driven behavior - Strategies for creating data driven organizations - A model-based approach to supporting self-service analytics and ending "data breadlines" - User experience design for data teams creating a data product for their organizations

1. Zach Taylor
Product Marketing
Connect. Describe. Explore.
DRIVE Conference
Mar. 12, 2015

2. • The importance of how data is delivered
• Strategies for creating data driven organizations
• Model-based approach
• User experience design for data teams
Intro

3. • Raised $30M Series B led by Meritech -- announced yesterday
• Bay Area Business Intelligence software founded 3 years ago
• In-database
• LookML
• Born-of-the-web
• Over 1 billion customers (kidding)
One Slide on Looker

4. 30 Seconds on My Background
• Finance for 3 years
• Learned to code
• Built web apps and founded a startup
• Joined Looker as a Data Analyst
• Now lead product marketing
• From Boston and went to the Super Bowl

5. Building Awesome Dashboards

6. Dashboards as a Starting Point
“We’ve discovered a problematic organizational pattern that often happens at
this point – data consumers need insights, and they ask for a “dashboard.” We
spend tons of time building it, and then we immediately forget it exists – it’s
not useful, because we didn’t know what we really wanted.
The part that’s missing in this pattern is exploration – giving data consumers
exposure to what is available, letting them discover real drivers, and allowing
them to “play around” with as many vectors and data points as possible.”
- Asana Engineering Blog

7. • Provide an environment that lets domain experts explore
• Enable data exploration
• Get all the data to the people with domain expertise
• Lower the bar to self-serving
• Provide a sufficiently flexible interface
• Once you find the metrics to rally around, encode them in great
visualizations and they will get used
Exploration

8. Watershed Moment
1.
2.
3.

9. The Problem with Data Breadlines
- Finite supply of analyst resources
- “Data-rich” and “data-poor”
- Data-poor don’t get the information
they need; they have to guess
- Q&A paradigm is painful and does
not scale

10. • Don’t firefight an endless queue of report
requests
• Build a reusable, accessible model
• Hones in on the right metrics
• Optimizes the user experience
• Enables a data-driven organization
• Alleviates supply gap of analyst resources
Build a Model

11. “...build a “model” around our data, centralizing definitions, sharing views, and
adding meta-data. Instead of writing queries all day, we can focus on building
out the model. Building a playground is a lot more fun than writing SQL.”
“Most of our business team are now able to explore data by themselves, even
those who don’t have any familiarity with SQL queries. Even better, they are
able to do this without needing any help from the data infrastructure team.”
Data Playground

12. Successful Model

13. Successful Model

14. Hierarchy of Needs
• How do you get people to self-serve
and explore?
• Moving up the hierarchy is hard
• Requires great design, willing
people and effective (sometimes
stringent) processes

15. • How data is delivered matters enormously for how well it is utilized
• Data teams need to think of themselves as designers
• Setting KPIs for adoption
• Need product experience on our team
• Refine the user experience and process around data to push through
barriers
Data People as Designers

16. How Important is Design?
Vs.
Average consumption rate per grapefruit?

17. Introduction of the GUI

18. • Great data strategies focus on delivery
• Data people need to think like designers
• Build a model of the data
• Enable data discovery for everyone
Conclusion

19. Thanks!