We live in a data first world. Give me more and more data. But what about the meaning of that data? How should the data be modeled so it can be easily understood and consumed by data scientist and analyst?

In this episode, Tim, Juan, and Ergest Xheblati, will live discuss why data modeling should be at the core of an enterprise.

This episode will also cover:
How data modeling is going to change the world moving forward.
How to start in data modeling
Why are data models such freakin divas?

We live in a data first world. Give me more and more data. But what about the meaning of that data? How should the data be modeled so it can be easily understood and consumed by data scientist and analyst?
In this episode, Tim, Juan, and Ergest Xheblati, will live discuss why data modeling should be at the core of an enterprise.
This episode will also cover:
<ul><li>How data modeling is going to change the world moving forward.</li>
 <li>How to start in data modeling</li>
 <li>Why are data models such freakin divas?</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.

Catalog & Cocktails: The Honest, No-BS Data Podcast

Data Models are Divas w/ Ergest Xheblati

Most quantum conversations are stuck on the timeline question: five years out? Two? Q-Day, the day current RSA encryption breaks, keeps getting pulled forward. But the actual risk to your data is already here. Adversaries are harvesting encrypted data today to decrypt it once quantum gets there. That makes this a data management problem right now.

John Licata, ServiceNow's futures director and quantum lead joins Juan and Tim, to unpack what this actually means for enterprise data teams. They get into where quantum computing does things classical AI genuinely can't do well: drug discovery, supply chain simulation, personalized medicine, where the quantum + AI combination changes everything, and who even owns quantum strategy? CISO? COOs? But the real argument is on the business value topic, not just focusing on risk mitigation which is where the real argument lives right now.

Most quantum conversations are stuck on the timeline question: five years out? Two? Q-Day, the day current RSA encryption breaks, keeps getting pulled forward. But the actual risk to your data is already here. Adversaries are harvesting encrypted data today to decrypt it once quantum gets there. That makes this a data management problem right now.
John Licata, ServiceNow's futures director and quantum lead joins Juan and Tim, to unpack what this actually means for enterprise data teams. They get into where quantum computing does things classical AI genuinely can't do well: drug discovery, supply chain simulation, personalized medicine, where the quantum + AI combination changes everything, and who even owns quantum strategy? CISO? COOs? But the real argument is on the business value topic, not just focusing on risk mitigation which is where the real argument lives right now.

Harvest Now, Decrypt Later: Why Quantum Is Already a Data Problem with John Licata

This is the takeaway episode with John Licata, ServiceNow's futures director and quantum lead where Juan and Tim unpack what quantum means for enterprise data teams.They get into where quantum computing does things classical AI genuinely can't do well: drug discovery, supply chain simulation, personalized medicine, where the quantum + AI combination changes everything, and who even owns quantum strategy? CISO? COOs? But the real argument is on the business value topic, not just focusing on risk mitigation which is where the real argument lives right now.

This is the takeaway episode with John Licata, ServiceNow's futures director and quantum lead where Juan and Tim unpack what quantum means for enterprise data teams.They get into where quantum computing does things classical AI genuinely can't do well: drug discovery, supply chain simulation, personalized medicine, where the quantum + AI combination changes everything, and who even owns quantum strategy? CISO? COOs? But the real argument is on the business value topic, not just focusing on risk mitigation which is where the real argument lives right now.

TAKEAWAY - Harvest Now, Decrypt Later: Why Quantum Is Already a Data Problem with John Licata

Shachar MEIR has spent 20 years fixing data teams and understanding why they fail. In this live episode, Shachar joins Juan and Tim to discuss the reason why they fail and what they should be doing in order to succeed. 

Shachar argues that data leaders default to what they can control (cough cough technology_ and underinvest in people, process, and culture. A new CDO comes in, migrates legacy databases to a cloud data platform, and two years later you have the same problems on a better platform.

We get into what's actually missing: building trust in data (which takes time and breaks fast), creating incentives so people actually use what data teams build, and spending real time in the business which is not asking what dashboards they need, but what problems they have. 

Topics discussed: 
Technology is not why data teams fail
Why data leaders default to technology
People, process and CULTURE
Data trust
Incentives
Understanding the business
Dashboard bloat
Self-service analytics
Dashboards aren't dead
What CDOs do well and what they miss

Shachar MEIR has spent 20 years fixing data teams and understanding why they fail. In this live episode, Shachar joins Juan and Tim to discuss the reason why they fail and what they should be doing in order to succeed.&nbsp;
Shachar argues that data leaders default to what they can control (cough cough technology_ and underinvest in people, process, and culture. A new CDO comes in, migrates legacy databases to a cloud data platform, and two years later you have the same problems on a better platform.
We get into what's actually missing: building trust in data (which takes time and breaks fast), creating incentives so people actually use what data teams build, and spending real time in the business which is not asking what dashboards they need, but what problems they have.&nbsp;
Topics discussed:&nbsp;
<ul>
<li aria-level="1">Technology is not why data teams fail</li>
<li aria-level="1">Why data leaders default to technology</li>
<li aria-level="1">People, process and CULTURE</li>
<li aria-level="1">Data trust</li>
<li aria-level="1">Incentives</li>
<li aria-level="1">Understanding the business</li>
<li aria-level="1">Dashboard bloat</li>
<li aria-level="1">Self-service analytics</li>
<li aria-level="1">Dashboards aren't dead</li>
<li aria-level="1">What CDOs do well and what they miss</li>
</ul>

Data Models are Divas w/ Ergest Xheblati

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Catalog & Cocktails: The Honest, No-BS Data Podcast

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