Anyone that works with data downstream in an organization has seen things go...wrong, while upstream managers and business leaders are being held accountable. Whether it's a failure in process, or something technically goes wrong, working with data is not always easy. What happened? How can we prevent it from happening again? What's next?
This talk, given at the Portland Data Science Group on October 27, 2016, uncovers 4 common foibles of working with organizational data.
• Who I am and what I am doing here
• What does business reality look
• Foible #1: Connecting silos
• Foible #2: Scheming the schema
• Foible #3: Ongoing integrity
• Foible #4: Making people care
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
• 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
Platform & Systems
Tools & Frameworks
Earning a unique role in
your customers’ lives.
From function, to value
It starts with a framework;
Builds a process;
Links with strategy;
Is built with technology;
And measures success.
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
If you are planning on success, plan
for scalability too.
Three major types:
Changes at the
Ex: Fields added,
Ex: Field itself
but what is in it
platform and tech.
Ex: A new platform
is added or is
Source: Girish Pancha