Have you ever had a tax form sent to the wrong address, a credit card with no suspicious activity get deactivated, or been billed for a service you’ve never used? If so, you may be the victim of poor data modeling.

Join Tim, Juan and Karen Lopez, aka @datachick from InfoAdvisors, to discuss what assumptions people and applications make about the simplest data. We’ll also try and answer the question, “why are phone numbers, and addresses so damn hard to model?!?”

This episode will feature:
Why modeling simple things is harder than it seems, and what we can do about it
The best and worst data modeling fails
If Sports Illustrated had an issue dedicated to data models, what would be on the cover?

Have you ever had a tax form sent to the wrong address, a credit card with no suspicious activity get deactivated, or been billed for a service you’ve never used? If so, you may be the victim of poor data modeling.
Join Tim, Juan and Karen Lopez, aka <a href='https://twitter.com/datachick'>@datachick</a> from InfoAdvisors, to discuss what assumptions people and applications make about the simplest data. We’ll also try and answer the question, “why are phone numbers, and addresses so damn hard to model?!?”
This episode will feature:
<ul><li>Why modeling simple things is harder than it seems, and what we can do about it</li>
 <li>The best and worst data modeling fails</li>
 <li>If Sports Illustrated had an issue dedicated to data models, what would be on the cover?</li>
</ul>

Catalog and Cocktails is the honest, No-BS, non-sales-y podcast about data and analytics. This is your unfiltered chat about everything interesting in data and analytics. Join Juan Sequeda and Tim Gasper to explore emerging topics and hear from thought leaders, practitioners and executives across the data and analytics space.

Catalog and Cocktails is the honest, No-BS, non-sales-y podcast about data and analytics. This is your unfiltered chat about everything interesting in data and analytics. Join Juan Sequeda and Tim Gasper to explore emerging topics and hear from thought leaders, practitioners and executives across the data and analytics space.