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Artwork for Eventual Consistency

Eventual Consistency | Your Reality Check on What's Actually Happening in Data

CorrDyn
Data Transformation
Duckdb
Incremental Processing
SQL Mesh
Tobiko Data
Artificial Intelligence
DBT
Motherduck
Cloud Computing
Data Warehousing
JSON Data
Data Science
Postgres
ETL Processes
Data Engineering
Machine Learning
IBM
Confluent
Software Supply Chain
DBT Labs

The data leader's fortnightly reality check. No hype. No hot takes for engagement. Just honest conversation about what's actually happening in data and what it means for the work you're doing.

Every two weeks, we pick the stories dominating your feed, the acquisitions, product launches, frameworks, and controversies and discuss them the way you would with your team: critically, honestly, and with... more

PublishesTwice monthlyEpisodes25Founded2 years ago
Number of ListenersCategories
NewsManagementBusinessTech News

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Artwork for Eventual Consistency

Latest Episodes

Every major AI lab has just bought itself a consulting arm. Ross Katz explains why that is not a flex, it is an admission that the model alone does not create value.

You have been told to "do something with AI" by year end, and now every systems in... more

Snowflake and Databricks held their flagship conferences within a fortnight of each other and both independently built their entire keynotes around the same claim: the bottleneck for enterprise AI is not the model, it is the context.

When two direc... more

The Big Four accounting firms are posting more job ads for AI specialists than for auditors. Graduate intake is down 30% at KPMG and 22% at Deloitte. Equity partners are being quietly demoted. The global chairman of PwC is telling the BBC he can't fi... more

When AI can produce a ten-page analytics report, spin up a data pipeline, or generate a plausible infrastructure assessment in minutes, a question starts nagging at everyone running a professional services business: what exactly are clients still pay... more

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Recent Guests

Jamil Bou Khair
Founder and CEO
Firezone
Episode: How Software Supply Chain Risk Became Everyone's Problem
Brian Manifold
Senior full stack engineer
Firezone
Episode: How Software Supply Chain Risk Became Everyone's Problem
James Winegar
AI infrastructure expert focusing on agentic systems
Episode: The New Plumbing: What MCP's Rise to Industry Standard Means for Enterprise Data Strategy
Mickey Peters
Former Energy Executive and Vistage Chair
Vistage; former Duke Energy executive
Episode: Power Before Code: The Energy Constraints Reshaping AI Infrastructure
Ross Katz
Industry expert guest discussing SaaS Apocalypse and data infrastructure
CorrDyn
Episode: 8 Ways to Survive the SaaSpocalypse
Matt Sekac
Head of data and analytics, WeLocalize
WeLocalize
Episode: “AI's Experimentation Era is Over” Says Davos
Toby Mao
CTO and co-founder of Tobiko Data
Tobiko Data
Episode: Enhancing Developer Efficiency with SQL Mesh | Featuring Toby Mao
Nicole Radziwill
Data strategist and author with extensive experience in data science and process management
Episode: People as Both the Problem and the Solution in Data | Featuring Nicole Radziwill

Host

Ross Katz
Host/industry expert providing practitioner perspectives; appears across multiple episodes

Reviews

5.0 out of 5 stars from 8 ratings
  • Excellent Insights

    Really great to hear another podcast from CorrDyn, James really knows his stuff

    Apple Podcasts
    5
    AdamHwales
    United Kingdom2 years ago

Listeners Say

Key themes from listener reviews, highlighting what works and what could be improved about the show.

Clear-eyed, practical take on data strategy that helps separate signal from hype.
Consistent focus on governance, risk, and enterprise impact.
Provides frameworks rather than buzzword hype, useful for decision-making.
Strong host–guest dynamic with real-world, actionable insights.

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Apple Podcasts
#188
New Zealand/News/Tech News

Talking Points

Recent interactions between the hosts and their guests.

“AI's Experimentation Era is Over” Says Davos
Q: What makes an AI Center of Excellence effective, and is it essential?
An effective center helps align leadership, establish value hypotheses, and concentrate influence to steer initiatives. It's not the only model, but having a centralized focus helps drive disciplined adoption while allowing room for bottom-up innovation.
“AI's Experimentation Era is Over” Says Davos
Q: How is WeLocalize using AI today, and what role does it play across the business?
AI is embedded across our core workflows, including translation, quality estimation, and orchestration of work at scale. It supports both client-facing products and internal product development, with human-in-the-loop practices to maintain quality.
“AI's Experimentation Era is Over” Says Davos
Q: What was your first reaction when you heard the experimentation era is over?
My takeaway was that the era isn't over in principle, but the way we measure progress must change—from counting pilots to proving value through decisions and investments. We need disciplined experimentation that informs real production outcomes.
How Software Supply Chain Risk Became Everyone's Problem
Q: How will AI changes affect defense and blue-team strategies as models get more capable?
AI could enable faster bug discovery and automated red-teaming, pushing defenders to develop autonomous, real-time defense and faster patching, while maintaining the need for human verification and verification workflows to avoid false positives.
Acceleration Without Stabilization: what AI is doing to data teams, according to the dbt Lab State of Analytics Engineering report
Q: So Ross, DBT Labs have just published its 2026 State of Analytics Engineering report. What's your takeaway and first reaction?
AI is accelerating data work, but this acceleration creates tensions between speed and stability. Trust and governance must be treated as core infrastructure to enable reliable, scalable AI-enabled data practices, and leaders must manage expectations and accountability as roles shift.

Audience Metrics

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Frequently Asked Questions About Eventual Consistency

What is Eventual Consistency about and what kind of topics does it cover?

This show curates practical, reality-grounded discussions about data leadership and enterprise data strategy. Episodes consistently cut through hype to examine platform choices, data governance, AI integration, and the real-world implications for data teams, architects, and executives. Listeners get candid analyses of vendor claims, architecture decisions, and how to execute transformations without overpromising results. A notable strength is its practitioner-focused lens, featuring data leaders and consultants who share concrete lessons from the field, including governance, risk, and operating models that actually move business outcomes forward.

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These podcasts share a similar audience with Eventual Consistency:

1. This American Life

How many episodes of Eventual Consistency are there?

Eventual Consistency launched 2 years ago and published 25 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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What guests have appeared on Eventual Consistency?

Recent guests on Eventual Consistency include:

1. Jamil Bou Khair
2. Brian Manifold
3. James Winegar
4. Mickey Peters
5. Ross Katz
6. Matt Sekac
7. Toby Mao
8. Nicole Radziwill

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