In this webinar we see why and how Tout – a fast-growing video platform – made the jump to Looker and Treasure Data, and solved their data stack issues. Slides cover: -The pitfalls of in-house solutions -The importance of companywide access to all data -The best way to optimize your data pipeline -The facts behind buying vs. building analytics infrastructure

1. Data Stack Considerations:
Build vs. Buy at Tout
July 14, 2016

2. Housekeeping
• We will do Q&A at the end.
• You should see a box on the right
side of your screen.
• There is a button marked “Q&A” on
the bottom menu.
• We will be recording this
• We will send you the recording
tomorrow.
• We will also send you the slides
tomorrow.
RecordingQ&A

3. Jad DeFanti
VP, Technical Operations
John Hammink
Developer Evangelist
Ming Liu
Sr. Software Architect
Erin Franz
Alliances Analyst
2
Meet Our Presenters
David Banker
Director, Product
Management

4. 4
AGENDA
1.
2.
3.
4.
Quick intro to Treasure Data
Quick intro to Looker
Build vs. Buy at Tout
Q & A

5. Treasure Data makes ….

6. WHO WE ARE

7. WHO WE ARE

8. BEFORE
• Data loss
• Inflexible
• Silos
• Complex Integrations
• High Costs
• High Time-To-Market
ETL Team
EDW Team
BITeam
End User
System

9. AFTER
OPTION 1

10. OPTION 2
AFTER

11. Make it easy for everyone
to find, explore and
understand
the data that drives your
business.
2

12. A DATA PLATFORM THAT DOES BOTH
Find, explore and understand all the data
Explore Everything
Find, explore and
understand all the data
Create Standards
Define your data and
business metrics
Any SQL Database
Analyze all of your data
where it is stored
Build a Data Culture
Anyone can ask and
answer questions
How is pipeline
for Q4?
Will we meet
our revenue
targets?
Which
campaigns
convert best?
Which rep is
converting
best?
Which customer
is at risk?
Can we speed
up our
operations?

13. THE TECHNICAL PILLARS THAT MAKE IT POSSIBLE
100% In Database
Leverage all your data
Avoid summarizing or moving it
Modern Web Architecture
Access from anywhere
Share and collaborate
Extend to anyone
LookML Intelligent
Modeling Layer
Describe the data
Create reusable and shareable
business logic

14. Leverage a Looker Block or
App or quickly implement a
custom deployment for a
complete analytics solution
Looker makes TD data
accessible and interactive for
anyone from Finance to
Marketing to Customer
Service
Leverage the TD platform in
real time with Looker to get
actionable insights to anyone
Full flexibility over defining
data at query time with
LookML w/o modeling ahead
of time.
Best of
Breed
Fast Time
to Value
Analytic
Flexibility
Data for
Everyone
Simplified Analytics, Powerful
Data Discovery.

15. 1
5
How Treasure Data & Looker saved us from our
Analytics stack and vendor
1
5

20. 2
0
Analytics & Tout Platform usage growth
• Tout utilized both a turnkey analytics solution and an
internal home-grown service
• Analytics events and costs skyrocketed in Q4 2015

21. 2
1
Legacy systems issues
• Single source vendor
• Home grown solution not reliable and difficult to support

22. 2
2
What problems were we trying to solve with analytics?
2
2
repetitive,
long term
unpredictive,
short term
customers'
predefined
dashboards
customers' ad-
hoc reports
requests
internal routine
reports
internal ad-hoc
reports
external, direct impact
internal, indirect impact
foundation
foundation

23. 2
3
What were our demands and costs?
2
3
customer demand internal demand
direct & indirect
Engineering / OPEX cost
vendor cost
our
options

24. 2
4
What to build?
buy one-stop
solution
(blackbox)
build custom
solution
(whitebox)
rent and integrate specialized
components (greybox)
less flexible
less time / effort
more expensive
more flexible
more time / effort
less expensive
Blackbox, Whitebox or something in between?

25. 2
5
What were the attributes of analytics reports required?
Charts
&
Report
s
Aggregated Data
Raw Data
smaller, faster,
comprehensible
bigger, slower,
incomprehensible
flexible, detailed
rigid, brief

26. 2
6
How we fixed the problem
• Completely re-think data analytics
Best of breed over single vendor and home-grown
solutions
• Outsource as much as possible
Scale-Out over Scale-Up

27. 2
7
What does our solution look like?
Data Collection &
Storage
Reporting Database Data
Analytics/Visualization
Primary Owner Treasure Data MySQL / Redshift Looker
Infrastructure Vendor & Customer Customer Vendor

28. 2
8
How does it work? Amazon
S3
Amazon
Redshift
Looker
Treasure
Data
coordinator
events
scaleable
receiver
Sinatra
Puma
Rack
TD logger
Fluentd
Tout’s logic
TD output
Tout’s config
Tout’s logic

29. 2
9
Keeping up with the business
Customers will adopt our services if we provide better
• Daily Reports
• Monthly Reports
• Better insights into Tout platform usage data

30. 3
0
Deliver Insight Quickly

31. 3
1
Deliver Customized Insights Quickly

32. 3
2
Room to Evolve
Where do we go from here?
• Customized and generic platform usage reports
• Predictive revenue analytics
• Analytics now open to all stakeholders
• Upsell Additional Analytics Reporting

33. 3
3
Summary
• Tout now meets its customers’ and internal stakeholders’ reporting
needs
• Tout analytics OPEX has been reduced by 50%
• Tout Engineering & Operations can now focus on applications &
infrastructure most relevant to our value to customers

34. Q&A
12

35. THANK YOU FOR JOINING
Recording and slides will
be posted.
We will email you the links
tomorrow.
See you next time!
Next from Looker Webinars:
Winning with Data on July 28
See how Treasure Data
and Looker work on your
data.
Visit treasuredata.com and
looker.com/free-trial or email
discover@looker.com.

36. THANK YOU!