1.
with Lars von Sneidern

2.
Hi! Thanks for letting me
crash the party.

3.
What’s up
tonight?
• Who I am and what I am doing here
• What does business reality look
like?
• Foible #1: Connecting silos
• Foible #2: Scheming the schema
• Foible #3: Ongoing integrity
• Foible #4: Making people care

4.
Who is this person?
• Yes, Lars is my real name
• I am the Customer Data and
Insights Lead for Connective DX
• What the heck does that mean?
• I make sailors blush
• I love bulleted lists

5.
About Us:
• 19 years old
• 80 people strong
• 2 offices (Portland & Boston)
• 5 “Best Places to Work” awards
• Recognized by Forrester as a leading Digital Experience Agency

6.
Experience
Strategy
Customer Data
& Insights
DX Strategy
& Roadmap
Technology Consulting
Data Consulting
Innovation
Analytics
Experience
Design
Customer Journey
Mapping
Content Strategy
Digital Experience
Design
Experience
Optimization
Technology
Platform & Systems
Consulting
Content Management
Application
Development
Global Content
Delivery
Mobile
Commerce
Digital
Enablement
DX7 Assessment
Tools & Frameworks
Product Acceleration
Training
& Education
Staffing
Connected Expertise

7.
Select technology
partners

8.
Select Clients

9.
Need
Compare
Discover
Research
Purchase
Decide
Use
Get Help
Share
Personalize
PartnerEvangelize
Tribe
Search
Customer
Experience
Journey
The Customer
Experience
Journey
Earning a unique role in
your customers’ lives.
From function, to value
to meaning.

10.
It starts with a framework;
Builds a process;
Establishes governance;
Links with strategy;
Is built with technology;
And measures success.

11.
Known user
attributes
Voice of
customer
Observed
behavior
Known user
opinions
Known user
behaviors
Touchpoint
opinions
Customer
insights

12.
Customer
Data
Platforms

13.
The reality of
“business” data

14.
What do we mean by business data?

15.
Foible #1:
Connecting Silos

16.
What are your silos?

17.
Customer
Support

18.
Connecting Data Silos
CRM
Web
Analytics
CMS
Email
Personalization
Cobweb
Ad
serve
Hub-and-Spoke
Customer
Data
Platform
Personalization
Testing
CRM
Web
Analytics
CMS
Email
Ad
serve
Testing

19.
Use case: How do we create a
single view of customer data?
Option 1:
Figure out and
use a universal
ID
Option 2:
Behavior and
cookie
matching

20.
You and UUIDs

21.
Customer
Support

22.
This can get big in
non-relational
systems

23.
HOLY SHIT
WHAT IS
GOOGLE DOING

24.
Who’s in charge of
your data?
…depends on who
you ask!

25.
Remember
Master Data
Management?

26.
These days many
people are talking
about Governance
instead

27.
Regardless, the idea
is having one
Source of Truth

28.
Foible #2: Scheming
the schema

29.
1. Do you have the right data?
2. Are you normal?
3. Can you scale?

30.
Do I have right data?

31.
What are you trying to accomplish?

32.
Remember
Data Dictionaries?
Yeah, let’s do that
more.

33.
To Normalize, or not?
IT IS A QUESTION!

34.
Pretty Normal
Too Normal?

35.
To Normal or to Not
Pros:
• Keeps data clean
• Is a best-practice
• It scales
Cons:
• Will cause table
bloat
• It’s exactly not easy
• It takes time

36.
What about
Scalability?

37.
I have seen several examples of
PostgreSQL systems that were
built to be quick and easy, but had
some major performance issues as
they didn’t grow out of the Proof of
Concept phase.
If you are planning on success, plan
for scalability too.

38.
Foible #3: Ongoing
integrity

39.
Noting is as it has
always been

40.
Data Drift
Three major types:
Structural:
Changes at the
source.
Ex: Fields added,
deleted, or
changed
Semantic:
The meaning
changes.
Ex: Field itself
doesn’t change,
but what is in it
does
Infrastructure:
Changes in
platform and tech.
Ex: A new platform
is added or is
changed
Source: Girish Pancha
http://www.cmswire.com/big-data/big-datas-hidden-scourge-data-drift/

41.
API “Jitter”

42.
Makes your
ETL, SOL

43.
So, what can you do
about it?

44.
checking

45.
Foible #4:
Making people care

46.
Developers need
____?

47.
Developers need
requirements.

48.
Business people
need ____?

49.
Business people
need insights.

50.
The key is
Empathy

51.
Thanks!