Hannes Mühleisen, creator of DuckDB, joins Juan and Tim to discuss why tables keep coming back and how the pendulum always swings. They cover the background of DuckDB, how it started, dive into the internals, when to use it and when not to use it. And of course, a bit of discussion on AI. Topics discussed
Tables as the basic abstraction
The pendulum from schemaless back to schema
Physics and performance
Install experience drives adoption
Scale up versus scale out
When to use DuckDB
Graphs
Governance of local compute
Semantics belongs to other layers
AI and agents
Building a database company
Do we need more database systems?

Hannes M&uuml;hleisen, creator of DuckDB, joins Juan and Tim to discuss why tables keep coming back and how the pendulum always swings. They cover the background of DuckDB, how it started, dive into the internals, when to use it and when not to use it. And of course, a bit of discussion on AI. Topics discussed
<ul>
<li aria-level="1">Tables as the basic abstraction</li>
<li aria-level="1">The pendulum from schemaless back to schema</li>
<li aria-level="1">Physics and performance</li>
<li aria-level="1">Install experience drives adoption</li>
<li aria-level="1">Scale up versus scale out</li>
<li aria-level="1">When to use DuckDB</li>
<li aria-level="1">Graphs</li>
<li aria-level="1">Governance of local compute</li>
<li aria-level="1">Semantics belongs to other layers</li>
<li aria-level="1">AI and agents</li>
<li aria-level="1">Building a database company</li>
<li aria-level="1">Do we need more database systems?</li>
</ul>

Tables Rock and DuckDB with Hannes Mühleisen

This is the takeaway episode with Hannes Mühleisen, creator of DuckDB who joined Juan and Tim to discuss why tables keep coming back and how the pendulum always swings. They cover the background of DuckDB, and so much more

This is the takeaway episode with Hannes M&uuml;hleisen, creator of DuckDB who joined Juan and Tim to discuss why tables keep coming back and how the pendulum always swings. They cover the background of DuckDB, and so much more

TAKEAWAY Tables Rock and DuckDB with Hannes Mühleisen

Richard Masters, Senior Managing Director and Head of AI Strategy at Ancora AI by Design and former VP of Data at Virgin Atlantic joins Juan and Tim to discuss how to tie data and AI work to business strategy.

The first basic question: what does the organization want to look like in three to five years, and what has to happen to get there? Platforms and models only matter if they serve that answer. And how do you measure? Setting a baseline is hard, slow work, and teams often skip it to start building. Without one, it is hard to tell whether the work is worth doing, and harder to ask that question once the build is underway.

We cover: starting with AI instead of a workflow or metric, running a pre-mortem, tracking evaluation scores instead of the business outcomes, governance engineering, and the roles that change as AI takes over work that used to be outsourced. 

Richard Masters, Senior Managing Director and Head of AI Strategy at Ancora AI by Design and former VP of Data at Virgin Atlantic joins Juan and Tim to discuss how to tie data and AI work to business strategy.
The first basic question: what does the organization want to look like in three to five years, and what has to happen to get there? Platforms and models only matter if they serve that answer. And how do you measure? Setting a baseline is hard, slow work, and teams often skip it to start building. Without one, it is hard to tell whether the work is worth doing, and harder to ask that question once the build is underway.
We cover: starting with AI instead of a workflow or metric, running a pre-mortem, tracking evaluation scores instead of the business outcomes, governance engineering, and the roles that change as AI takes over work that used to be outsourced.&nbsp;

Start With the Business Metric, Not the AI with Richard Masters

This is the takeaway episode with Richard Masters, Senior Managing Director and Head of AI Strategy at Ancora AI by Design and former VP of Data at Virgin Atlantic where he joins Juan and Tim to discuss how to tie data and AI work to business strategy.

We cover: starting with AI instead of a workflow or metric, running a pre-mortem, tracking evaluation scores instead of the business outcomes, governance engineering, and the roles that change as AI takes over work that used to be outsourced, and so much more. 

This is the takeaway episode with Richard Masters, Senior Managing Director and Head of AI Strategy at Ancora AI by Design and former VP of Data at Virgin Atlantic where he joins Juan and Tim to discuss how to tie data and AI work to business strategy.
We cover: starting with AI instead of a workflow or metric, running a pre-mortem, tracking evaluation scores instead of the business outcomes, governance engineering, and the roles that change as AI takes over work that used to be outsourced, and so much more.&nbsp;

TAKEAWAY Start With the Business Metric, Not the AI with Richard Masters

In this special rant episode, Sonny Rivera joins Juan and Tim during a live recording and rant about AI-generated dashboards, semantic layers, and what it takes to trust an answer. The situation: dashboards slop is easy to build which makes foundation matter more, not less. We discussed: 
Building a dashboard was never the hard part. Being able to explain where a number came from is.
Speed without a governed foundation produces wrong answers faster. As Sonny put it, “fast and wrong is still wrong.”
Modeling data is really modeling the business. The job has not changed. How it gets done is changing.
A single source of truth did not hold up. Favors an interoperable set of semantic layers and context, with shared definitions where people actually care.
Logic written in the moment, in a dashboard or a pipeline, often never makes it back into the semantic layer. Closing that loop is the gap to fix.
Friction between teams is a sign that a definition matters. Make the differences visible rather than forbidding them.
Trust is what data leaders can least afford to lose, which is why testing belongs in dashboards too.
Writing code is no longer the slow part. Product management and testing are becoming the bottlenecks.

In this special rant episode, Sonny Rivera joins Juan and Tim during a live recording and rant about AI-generated dashboards, semantic layers, and what it takes to trust an answer. The situation: dashboards slop is easy to build which makes foundation matter more, not less. We discussed:&nbsp;
<ul>
<li aria-level="1">Building a dashboard was never the hard part. Being able to explain where a number came from is.</li>
<li aria-level="1">Speed without a governed foundation produces wrong answers faster. As Sonny put it, &ldquo;fast and wrong is still wrong.&rdquo;</li>
<li aria-level="1">Modeling data is really modeling the business. The job has not changed. How it gets done is changing.</li>
<li aria-level="1">A single source of truth did not hold up. Favors an interoperable set of semantic layers and context, with shared definitions where people actually care.</li>
<li aria-level="1">Logic written in the moment, in a dashboard or a pipeline, often never makes it back into the semantic layer. Closing that loop is the gap to fix.</li>
<li aria-level="1">Friction between teams is a sign that a definition matters. Make the differences visible rather than forbidding them.</li>
<li aria-level="1">Trust is what data leaders can least afford to lose, which is why testing belongs in dashboards too.</li>
<li aria-level="1">Writing code is no longer the slow part. Product management and testing are becoming the bottlenecks.</li>
</ul>

Dashboard Slop rant with Sonny Rivera

Nick Zervoudis, data product manager, trainer, and consultant at Value from Data & AI, joins Juan and Time to talk about why many data teams end up working like a service desk and what to do about it. The answer is: DO DISCOVERY! In this conversation, we cover how a service desk model breaks down when a request can’t be described in a few words, why dashboards get opened once and then forgotten, and how product thinking differs from project management in data work. We also discuss how to start doing discovery without a full transformation, and what AI does and doesn’t change about that work.

Nick Zervoudis, data product manager, trainer, and consultant at Value from Data &amp; AI, joins Juan and Time to talk about why many data teams end up working like a service desk and what to do about it. The answer is: DO DISCOVERY! In this conversation, we cover how a service desk model breaks down when a request can&rsquo;t be described in a few words, why dashboards get opened once and then forgotten, and how product thinking differs from project management in data work. We also discuss how to start doing discovery without a full transformation, and what AI does and doesn&rsquo;t change about that work.

How data teams become trusted business partners with Nick Zervoudis

This is the takeaway episode with Nick Zervoudis, data product manager, trainer, and consultant at Value from Data & AI, joins Juan and Time to talk about why many data teams end up working like a service desk and what to do about it. The answer is: DO DISCOVERY! 

This is the takeaway episode with Nick Zervoudis, data product manager, trainer, and consultant at Value from Data &amp; AI, joins Juan and Time to talk about why many data teams end up working like a service desk and what to do about it. The answer is: DO DISCOVERY!&nbsp;

TAKEAWAY How data teams become trusted business partners with Nick Zervoudis

Mohammed Aaser, former chief data officer at McKinsey and former chief data strategy officer at Domo, recently visited Juan and shared his framework on talent in the AI era. It was incredibly insightful and we asked if he could come back to the podcast (after 5 years!) His argument is that the potential of AI will be unlocked by humans because humans understand the problems, and are driven/motivated to solve the problems. 

In this episode, Mohammed lays out a framework for talent in the AI era. Automation is already taking over the known, repeatable work. What remains is the unknown, and that takes people who keep learning and who take initiative. The framework plots people on two dimensions, learning and drive. You have Doers, Philosophers, Commanders, Hackers, Strategist, Innovators, Game changers and more. Topics discussed
Automation and the innovation engine
The known versus the unknown
Two dimensions of talent
The talent quadrants
The multiplier effect
Commanders and scaling
Environments that don’t build initiative
Rarity of high-potential people
Investing in human potential
The human mind as the limit
Critical thinking through discomfort

Mohammed Aaser, former chief data officer at McKinsey and former chief data strategy officer at Domo, recently visited Juan and shared his framework on talent in the AI era. It was incredibly insightful and we asked if he could come back to the podcast (after 5 years!) His argument is that the potential of AI will be unlocked by humans because humans understand the problems, and are driven/motivated to solve the problems.&nbsp;
In this episode, Mohammed lays out a framework for talent in the AI era. Automation is already taking over the known, repeatable work. What remains is the unknown, and that takes people who keep learning and who take initiative. The framework plots people on two dimensions, learning and drive. You have Doers, Philosophers, Commanders, Hackers, Strategist, Innovators, Game changers and more. Topics discussed
<ul>
<li aria-level="1">Automation and the innovation engine</li>
<li aria-level="1">The known versus the unknown</li>
<li aria-level="1">Two dimensions of talent</li>
<li aria-level="1">The talent quadrants</li>
<li aria-level="1">The multiplier effect</li>
<li aria-level="1">Commanders and scaling</li>
<li aria-level="1">Environments that don&rsquo;t build initiative</li>
<li aria-level="1">Rarity of high-potential people</li>
<li aria-level="1">Investing in human potential</li>
<li aria-level="1">The human mind as the limit</li>
<li aria-level="1">Critical thinking through discomfort</li>
</ul>

Game Changers: The Talent Imperative for the AI Era with Mohammed Aaser

This is the takeaway episode with Mohammed Aaser, former chief data officer at McKinsey and former chief data strategy officer at Domo. He recently visited Juan and shared his framework on talent in the AI era. It was incredibly insightful and we asked if he could come back to the podcast (after 5 years!) His argument is that the potential of AI will be unlocked by humans because humans understand the problems, and are driven/motivated to solve the problems. 

This is the takeaway episode with Mohammed Aaser, former chief data officer at McKinsey and former chief data strategy officer at Domo. He recently visited Juan and shared his framework on talent in the AI era. It was incredibly insightful and we asked if he could come back to the podcast (after 5 years!) His argument is that the potential of AI will be unlocked by humans because humans understand the problems, and are driven/motivated to solve the problems.&nbsp;

TAKEAWAY Game Changers: The Talent Imperative for the AI Era with Mohammed Aaser

How do leaders preserve executive trust and credibility? Dora Boussias, executive advisor and former data executive returns to the podcast to unpack this question. Her answer: protect your judgement. 

In this episode, Dora presents the trust equation that most leaders grew up with: expertise + track record + judgment. Dora’s point is that the equation still holds, but each part now means something different. Nobody will out-know AI, so expertise is less about what you know and more about asking the right questions and challenging assumptions. A track record is harder to read when you can’t tell whether a good result came from you or from the model. Judgment carries the most weight now, and it’s the part leaders are most likely to hand off without noticing. Topics discussed: 
Trust equation under AI
Expertise is changing
Track record is harder to read
Judgment carries the most weight
Decision fog
Speed isn’t everything
Ford’s rehiring of experienced engineers
Business fundamentals matter more
Alignment and accountability are cross-functional
Real value is “so what”

How do leaders preserve executive trust and credibility? Dora Boussias, executive advisor and former data executive returns to the podcast to unpack this question. Her answer: protect your judgement.&nbsp;
In this episode, Dora presents the trust equation that most leaders grew up with: expertise + track record + judgment. Dora&rsquo;s point is that the equation still holds, but each part now means something different. Nobody will out-know AI, so expertise is less about what you know and more about asking the right questions and challenging assumptions. A track record is harder to read when you can&rsquo;t tell whether a good result came from you or from the model. Judgment carries the most weight now, and it&rsquo;s the part leaders are most likely to hand off without noticing. Topics discussed:&nbsp;
<ul>
<li aria-level="1">Trust equation under AI</li>
<li aria-level="1">Expertise is changing</li>
<li aria-level="1">Track record is harder to read</li>
<li aria-level="1">Judgment carries the most weight</li>
<li aria-level="1">Decision fog</li>
<li aria-level="1">Speed isn&rsquo;t everything</li>
<li aria-level="1">Ford&rsquo;s rehiring of experienced engineers</li>
<li aria-level="1">Business fundamentals matter more</li>
<li aria-level="1">Alignment and accountability are cross-functional</li>
<li aria-level="1">Real value is &ldquo;so what&rdquo;</li>
</ul>

Preserve Executive Trust by Protecting Your Judgement with Dora Boussias

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

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