The slides accompanying Clancy Childs' talk at Measurecamp V (2014) in London. Might be missing a lot if you weren't at the session, but basically covering some of the design decisions, pitfalls, technology choices and requirements when choosing to build your own analytics / eventing platform and data warehouse.

1. BYO/DIY
Analy,cs
Pla1orm
Clancy
Childs
Founding
Partner,
Inderus
(Google
Analy,cs
Refugee)
!
clancy@inderus.com
@cchilds
-­‐
@inderus

2. My
Past
Life

3. What
is
in
the
Big
Mac
Sauce?
hLp://inder.us/big-­‐mac-­‐recipe

4. WHY
would
you
ever
WANT
to
build
your
own
Analy,cs
Solu,on?
“See all that stuff in there, Homer?
That’s why your robot never worked.”

5. Tools
Are
Generally
Good
Things

6. The
Right
Tool
for
the
Job

7. …but
eagerness
to
use
a
tool
can
be
at
the
cost
of
geWng
the
job
done
correctly

8. Why
Some
Companies
“Roll
Their
Own”
Analy,cs
• End-­‐to-­‐end
customisa,on
(collec,on,
processing
and
repor,ng)
• Complete
control
and
governance
of
data
• Integra,ons
with
other
opera,onal
and
repor,ng
systems
• Ability
to
make
their
own
mistakes
on
their
own
terms

9. An
Insanely
Simplified
Analy,cs
Processing
Model
Collection
Processing
Enrichment
Storage Extraction Visualisation

10. An
Insanely
Simplified
Analy,cs
Processing
Model
Collection
Processing
Enrichment
Storage Extraction Visualisation

11. Collec,on
• First
vs.
Third
Party
beacons
• Client
vs.
Server
Side
collec,on
(over
GTM’d?)
• Opera,onal
By-­‐Products
(Logging)
• Snowplow,
Logstash,
Kinesis,
Kaaa(?)

12. An
Insanely
Simplified
Analy,cs
Processing
Model
Collection
Processing
Enrichment
Storage Extraction Visualisation

13. Processing
and
Enrichment
• Sessioniza,on
and
User
S,tching
• Processing
Schedules
and
Goals
(Lambda
Architecture?)
• Reprocessing
vs
“Golden”
Immutability
• Captured
Foreign
Keys
(gclid,
IP
address,
etc.)
• MapReduce,
Storm,
Flume…

14. An
Insanely
Simplified
Analy,cs
Processing
Model
Collection
Processing
Enrichment
Storage Extraction Visualisation

15. Storage

16. An
Insanely
Simplified
Analy,cs
Processing
Model
Collection
Processing
Enrichment
Storage Extraction Visualisation

17. Query/Extract
and
Visualize
• SQL
is
generally
much
easier
than
anything
else.
• Prototyping
with
Pandas
/
R
• Produc,on
Dashboarding
with
Visualiza,on
tools
• Char,o,
Looker,
Tableau,
Klipfolio,
Legronic,
others?

18. Thank
You!
Clancy Childs - @cchilds
Inderus - @inderus
clancy@inderus.com