Date: 16th November 2017 Location: Self-Service Analytics Theatre Time: 13:50 - 14:20 Speaker: Martin Zerbib Organisation: Looker

1. The 3rd Wave of Business Intelligence
Ingredients for an Agile Stack

2. 2
Business users
have a need for
governed data at scale

3. … but traditional
approaches haven’t
delivered
3
(why not?)

5. Oracle
(‘77)
Teradata
(‘79)
PostgreSQL
(‘86)
Cognos
(‘82)
Microstrategy
(‘89)
Business
Objects
(‘90)
Legacy providers were reliable, but slow
MySQL
(‘95)

6. … creating a data bottleneck
NEXT!
Analyst

8. 8
PostgreSQL
(‘86)
MySQL
(‘95)
Cognos
(‘82)
Microstrategy
(‘89)
Business
Objects
(‘90)
Qlik
(‘93)
Tableau
(‘03)
Alteryx
(‘06)
Talend
(‘07)
Frustrated users got their own tools
Oracle
(‘77)
Teradata
(‘79)

9. … but logic diffuses into silos
What is
accountable
revenue?
Does this
exclude cancelled
items?
What is an
active user?
How do we
calculate failure
rate?

10. 10
PostgreSQL
(‘86)
Vertica
(‘05)
BigQuery
(‘11)
Snowflake
(‘12)
Redshift
(‘12)
Hadoop
(‘05)
MySQL
(‘95)
Cognos
(‘82)
Microstrategy
(‘89)
Business
Objects
(‘90)
Qlik
(‘93)
Tableau
(‘03)
Alteryx
(‘06)
Talend
(‘07)
Meanwhile, data technology grows...
Oracle
(‘77)
Teradata
(‘79)

12. 12
PostgreSQL
(‘86)
Vertica
(‘05)
BigQuery
(‘11)
Snowflake
(‘12)
Redshift
(‘12)
Hadoop
(‘05)
MySQL
(‘95)
Cognos
(‘82)
Microstrategy
(‘89)
Business
Objects
(‘90)
Qlik
(‘93)
Tableau
(‘03)
Alteryx
(‘06)
Talend
(‘07)
Looker: built for today’s world
Oracle
(‘77)
Teradata
(‘79)
Looker
(‘12)

13. ❏ “Near-instant, near-infinite”
compute power
Elastic databases provide…
❏ Cheap infinite storage -
separate from compute
❏ Only pay for what you use
Ingredient #1:
A modern, powerful, elastic warehouse
SaaS Apps
Transactional DB
ERP Systems
Web Data
Data: Raw or
lightly modeled

14. Elastic Data
Warehouse
Companies start by
moving data into a
scalable warehouse...
SaaS Apps
Transactional DB
ERP Systems
Web Data

15. Elastic Data
Warehouse
? ?
Data
Marts
Cubes, Extracts
...but often end up
re-creating the same
problems
Companies start by
moving data into a
scalable warehouse...
? ?
SaaS Apps
Transactional DB
ERP Systems
Web Data

16. Ingredient #2:
Eliminate the extract, and connect live to your data
Live queries provide…
❏ Data is never out-of-date
❏ You can always drill to see the full
detail (e.g. individual invoices)
❏ Data never lives on a laptop - more
secure, easier to manage
Live queries
Data: Raw or
lightly modeled
SaaS Apps
Transactional DB
ERP Systems
Web Data

17. Live queries
What is
accountable
revenue?
Does this
exclude cancelled
items?
Data: Raw or
lightly modeled
SaaS Apps
Transactional DB
ERP Systems
Web Data

18. Live queries
LookML
Data: Raw or
lightly modeled
SaaS Apps
Transactional DB
ERP Systems
Web Data
ACCOUNTABLE REVENUE
= SUM(invoice_lines.invoice_lines_item)
WHERE
( invoice_code between 20001 and 29999
OR code = 99999)
AND charge_type != ‘ADJUSTMENT’
AND updated_at IS NOT NULL

19. Ingredient #3:
LookML - a modern logical data modelling layer
LookML provides…
❏ One single place to manage
business logic
❏ Live-powers all reports
(interactive data dictionary)
❏ Developer collaboration &
version control
Live queries
LookML
Data: Raw or
lightly modeled
SaaS Apps
Transactional DB
ERP Systems
Web Data

20. Extracts still occur when users
want data outside of a BI tool...
Live queries
LookML
Data: Raw or
lightly modeled
SaaS Apps
Transactional DB
ERP Systems
Web Data

21. ...unless those tools can interact
directly with the data
Live queries
LookML
Data: Raw or
lightly modeled
SaaS Apps
Transactional DB
ERP Systems
Web Data

22. Ingredient #4:
Robust platform (HTML5, API, webhooks…)
Platform provides...
❏ Take action directly
from the data
❏ Data where you want it,
when you need it
Live queries
LookML
❏ Work in the browser and
share with URLs
Data: Raw or
lightly modeled
SaaS Apps
Transactional DB
ERP Systems
Web Data

23. ❏ Work in the browser and
share with URLs
❏ Data where you want it,
when you need it
❏ Take action directly
from the data
❏ One single place to
manage business logic
❏ Live-power all reports as
an interactive data
dictionary
❏ Developer collaboration
and version control
❏ Data is never out of date
❏ Always drill to see the
full detail
❏ Data never lives on a
laptop - easier to
manage, more secure
Elastic Database Live Connect LookML Platform
❏ Cheap infinite storage,
separate from compute
❏ Near-instant,
near-infinite computing
power
❏ Only pay for what you
use
4 Ingredients for an Agile Stack
Governed self-service data at scale

24. Growing Customer Base
eCommerce Technology Marketplaces Financial Services Media & Ad Tech

25. Customer Stories
“We had results within
days...we’re able to build out all
the analytical tools our
pharmacies needed around key
operational data”
Chief Information Officer
“We wanted to facilitate
people answering questions
themselves, so we can focus on
the things we want to do and
enjoy”
Director, Business Intelligence

26. Thank you!
26