Date: 13th November 2018 Location: Self-Service Analytics Theatre Time: 12:30 - 13:00 Speaker: Joel McKelvey Organisation: Looker About: Companies that use data well are more efficient, effective, and profitable. Unfortunately, most organizations struggle to keep up with the changing supply of data — and the growing business demands for that data. The key is to connect data supply to data users in a way that scales, supports existing workflows, and serves as a foundation for the future. This session will explore how to bring data to users where and when they need it without sacrificing data governance or unified metrics. This session will also present proven ways to build a data foundation for your organisation that can support future changes in both data supply and data demand. Specifically, attendees will discover: • The key considerations to driving the most value from data, including: self-service, governance, custom interfaces, modeling, and connections to existing business systems. • How to provide users access to data in a way that naturally fits in their existing workflows and allows users to take immediate action. • How companies like Deliveroo and King extract critical business insights from growing data and deliver those insights to their business users.

1. FIGHTING DATA CHAOS
Joel McKelvey, Director of Product Marketing, Looker | November 13, 2018
CONNECTING USERS TO DATAAT SCALE

2. $177.5M in funding
CapitalG, Geodesic, Redpoint, First
Round, Goldman Sachs, Kleiner Perkins,
Meritech, Sapphire, PivotNorth
Global Offices
Santa Cruz, San Francisco,
Dublin, London, Tokyo,
New York, Boulder, Chicago
Major Partnerships
Google, Amazon,
Cloudera, Microsoft,
HPE, IBM
5 of 10 Fortune10 use
Looker
Over 1600
customers
600 + employees

3. Trends in Data Supply
§ Data doubles every 18 months
§ Proliferating data sources
§ Increased heterogeneity
§ Accelerated pace of change

4. Trends in Data Demand
DevOps
Engineer
DataDriven
Product
Manager
Financial
Analyst
Customer
Success
Manager
Sales &
Revenue
Ops Analyst
Quantitative
Marketer
DevOps
Engineer
DataDriven
Product
Manager
Customer
Success
Manager
Logistics
Manager
§ Increasing numbers of users
§ New data-driven roles
§ More diversity of requirements
§ Accelerated pace of change

5. Connecting People to Data – The Analytics Challenge
DevOps
Engineer
DataDriven
Product
Manager
Financial
Analyst
Customer
Success
Manager
Sales &
Revenue
Ops Analyst
Quantitative
Marketer
DevOps
Engineer
DataDriven
Product
Manager
Customer
Success
Manager
Logistics
Manager
?
The
Data
Team

6. Connecting People to Data – The Analytics Challenge
DevOps
EngineerDataDriven
Product
Manager
Financial
Analyst
Customer
Success
Manager
Sales &
Revenue
Ops Analyst
Quantitative
Marketer
DevOps
Engineer
DataDriven
Product
Manager
Customer
Success
Manager
Logistics
Manager
!
The
Data
Team

7. Point Solutions and Department-Level Analytics
DevOps
EngineerDataDriven
Product
Manager
Financial
Analyst
Customer
Success
Manager
Sales &
Revenue
Ops Analyst
Quantitative
Marketer
DevOps
Engineer
DataDriven
Product
Manager
Customer
Success
Manager
Logistics
Manager
The
Data
Team
!
!
!
!
!
!

8. The Platform Approach
DevOps
EngineerDataDriven
Product
Manager
Financial
Analyst
Customer
Success
Manager
Sales &
Revenue
Ops Analyst
Quantitative
Marketer
DevOps
Engineer
DataDriven
Product
Manager
Customer
Success
Manager
Quantitative
Marketer
The
Data
Team
Modern
Database
Platform
Services
Presentation
Layer

9. Describing the Platform
Modern
Database
Platform
Services
Presentation
Layer
• In-database architecture
• MPP database support
• Integrations (security, etc.)
• Data centralization focus
• Extract (transform) Load
• Database agnostic
• Common data model
• Repeatability
• Control, governance
• Comprehensive analytics
• Inheritance, sharing
• Extensibility
• Self-service
• Explorability/discoverability
• Automation
• Integrated with 3rd party platforms
• Embedded analytics
• Customizability

10. Active Users
Data Team
Ad-hoc requests (per week)
Straight talk: Analytics scales faster than your team
Historical Data. Extrapolated.

11. Active Users
Data Team
Ad-hoc requests (per week)
Looker Implementation
The Platform at Work: Scaling Looker

12. Old Approach Platform Approach
● Different BI tools across the company
● Inconsistent results
● Sluggish performance
● Platform provides single source of truth
● Common process for interpreting data
● Rapid insights, company-wide adoption
Jonathan Palmer, Business Intelligence Lead
Hundreds of reports users have
built and scheduled for themselves
would have taken our data team a
year or more to create before
Looker.
©Looker2018.Confidential

13. “Looker has freed our
time to do far more
useful work.”
Andrew Dunmall
Analytics Product Consultant
©Looker2018.Confidential

14. “People began
customizing reports and
exploring the data much
faster than we ever
expected.”
Will Sprunt
Head of Business Intelligence
©Looker2018.Confidential

15. “There’s basically no
end to how we can
continue to evolve
Looker –- which is
really exciting.”
Tom Hillman
Paid Social Manager
©Looker2018.Confidential

16. Blissful BI with
Learn more at the session “Blissful BI with Brandwatch"
Data Ops Theatre, 13 Nov, 2.30-3.00pm

17. Questions? Please visit stand #437 for more information