episodic 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 one question in mind: "What does this actually mean for my world?"

We're not here to sell you courses, predict the future, or tell you the sky is falling. We're here to cut through vendor claims that everything is "revolutionising" something, LinkedIn posts oscillating between doom and humble-brags, and tech journalism that treats every product launch like it's world-changing.

This is for VPs of Data, Analytics Directors, Data Engineering Managers, and senior practitioners who need to stay informed but don't have time to wade through whitepapers and noise. People making real decisions: Should we migrate to that warehouse? Is this ML use case worth it, or just shiny object syndrome? Why is everyone talking about this framework when it doesn't solve our actual problem?

In 20 minutes, you'll know what's worth your attention and what you can safely ignore. You'll get the perspective to make better decisions, ask vendors better questions, and avoid getting swept up in whatever trend is dominating feeds this week.

You'll hear from practitioners and consultants who've been in the room when these decisions go right and when they go spectacularly wrong. We know what the press release says. We also know what actually happens six months later.

Because in data, like in distributed systems, consistency is hard. But eventually, reality catches up with the hype.


]]> CorrDyn Eventual Consistency | Your Reality Check on What's Actually Happening in Data 2024 CorrDyn CorrDyn false CorrDyn jason.bradwell@corrdyn.com en https://www.corrdyn.com/ The threat isn't coming from outside your perimeter. It's already inside, embedded in the open source libraries your engineers pulled in last quarter, the routers running on your network, the security tooling sitting in your CI/CD pipeline.

In this episode of Eventual Consistency, host James Winegar is joined by Jamil Bou Khair, founder and CEO of Firezone, and Brian Manifold, senior full stack engineer at Firezone, to unpack what software supply chain security actually looks like in practice and why most enterprises are still building their defenses for a threat model that no longer reflects reality.

The conversation is grounded in a real incident: the March 2026 Trivy vulnerability, in which attackers exploited a misconfiguration in Aqua Security's GitHub Actions environment, extracted a privileged access token, and used it to publish a malicious binary that was live in distribution channels for nearly three hours. 

They also discuss the hardware dimension of supply chain risk, with the US government's ban on foreign-made routers, and the reality that manufacturing on US soil doesn't solve the chip provenance problem. 

They dig into the tension between moving fast and maintaining operational security, drawing on Jamil's experience scaling Firezone from a startup with three engineers to a team with GitHub Enterprise security policies enforced at the repo level.

The episode closes with the practical architecture of defensibility: why blast radius reduction and zero trust segmentation matter more than perimeter security in an AI-accelerated threat environment, how Firezone approaches dependency management including cooldown periods and IP allow listing across SaaS platforms, and why the industry may be approaching a moment where writing your own dependencies rather than pulling in shared libraries, becomes a legitimate security strategy.

About the Host

James Winegar is a data consultant who has spent years in the trenches helping enterprise organizations actually implement the technologies that vendors promise will revolutionize their business. He specializes in data infrastructure, real-time systems, and the practical realities of what works when the proof of concept becomes production. His approach is skeptical, pragmatic, and focused on the economics of technology decisions, a lens he brings to bear throughout this episode on the real costs of getting MCP wrong and what it actually takes to make AI agents useful in a production enterprise environment.

About the Guests

Jamil Bou Khair is the Founder and CEO of Firezone, a zero trust network access platform. Jamil brings a founder's perspective on the operational security trade-offs that real engineering teams face when moving fast in a threat environment that is moving faster.

Connect with Jamil on LinkedIn: https://www.linkedin.com/in/jamilbk/

Brian Manifold is a Senior Full Stack Engineer at Firezone. Brian works across the stack on security architecture and has direct experience with the dependency management, access control, and incident response challenges discussed in this episode.

Connect with Brian on LinkedIn: https://www.linkedin.com/in/brian-manifold-536a0a3a/

Connect with us: 

  • Sponsor: https://www.corrdyn.com/ a data consultancy
  • Connect with James Winegar on LinkedIn: https://www.linkedin.com/in/james-winegar/
]]> How Software Supply Chain Risk Became Everyone's Problem How Software Supply Chain Risk Became Everyone's Problem 00:34:25 9f83adbc-e514-414c-a14a-f13e0e7d0c34 7 2 full false https://www.corrdyn.com/ Thu, 23 Apr 2026 17:00:33 +0000 In March 2026, Digital Applied reported that Anthropic's Model Context Protocol had crossed 97 million installs in just 16 months, a faster adoption curve than most enterprise infrastructure standards ever achieve. OpenAI, Google, and Microsoft are all now shipping MCP-compatible tooling. What started as one company's open standard has quietly become the default interface between AI agents and the systems they work with.

But is 97 million installs the moment a standard becomes infrastructure or just a very large number? In this episode of Eventual Consistency, Ross Katz sits down with James Winegar to unpack what MCP's rise actually means for the companies building on it, the enterprises adopting it, and the data leaders who are going to be asked to make decisions about it.

James argues that the standardization happened much earlier than most people realize; the install count is a lagging indicator, not the inflection point. The real question now isn't whether to pay attention to MCP, but how to build for a world where it's the default. And the answer, he contends, isn't to throw AI at your raw source systems and hope for the best. The companies that will win are the ones that do the foundational work first: getting data into a warehouse, modeling it properly, and then giving AI agents a well-scaffolded, cost-efficient interface to query against, rather than burning compute calling out to Salesforce, your ERP, and five other SaaS platforms in real time and hoping the answer comes back with reasonable fidelity.

The episode also gets into the tension between MCP and CLI tooling, when each is the right interface, why startups are naturally gravitating toward MCP to get to market fast, and why the security and authentication story around MCP is still catching up to what enterprise compliance actually requires. James draws a sharp distinction between MCP servers that authenticate as a privileged service account and those that can actually propagate user-level permissions and explains why that distinction matters enormously once HIPAA, SOC 2, or SEC compliance enters the conversation.

Ross and James close with a provocation: by 2028, what does the world look like for a data team that treated MCP as someone else's infrastructure problem?

About the Hosts

Ross Katz brings a background in analytics and data strategy, working with companies to cut through the noise and focus on what actually drives business value. With experience spanning industries such as e-commerce, education, biotech, and finance, as well as the evolving landscape of AI-enabled work, he focuses on the intersection of data capabilities and business outcomes. He's particularly interested in how shifts in technology change not just what's possible but also how people think about and use data in their daily work.

James Winegar is a data consultant who has spent years in the trenches helping enterprise organizations actually implement the technologies that vendors promise will revolutionize their business. He specializes in data infrastructure, real-time systems, and the practical realities of what works when the proof of concept becomes production. His approach is skeptical, pragmatic, and focused on the economics of technology decisions, a lens he brings to bear throughout this episode on the real costs of getting MCP wrong and what it actually takes to make AI agents useful in a production enterprise environment.

Connect with us: 

]]> The New Plumbing: What MCP's Rise to Industry Standard Means for Enterprise Data Strategy The New Plumbing: What MCP's Rise to Industry Standard Means for Enterprise Data Strategy 00:54:34 c1de107a-b7fc-47d1-8758-25a7a71d33ed 6 2 full false https://www.corrdyn.com/ Thu, 09 Apr 2026 17:08:31 +0000 In early March, two major retailers made headlines with strategies that look like opposite bets on the future. Best Buy announced a partnership with OpenAI, opening its product catalog to ChatGPT and supporting Google's Universal Commerce Protocol, positioning itself to be discovered and purchased through AI agents, not just human browsers. Target, meanwhile, announced plans to open more than 30 new physical stores in 2026, backed by a $5 billion capital investment plan that includes expanded fulfillment, food and beverage, and same-day delivery infrastructure built in from the ground up.

On the surface, these look like diverging strategies. In this episode of Eventual Consistency, we discuss the case that they're actually two versions of the same underlying bet on where data advantage lives in the next decade of retail.

Ross Katz breaks down what it actually takes in the back end for Best Buy to make its product catalog legible to AI agents: clean, structured product data with consistent taxonomy, real-time inventory APIs capable of handling agent-scale request volumes, programmatic pricing that can respond without a human in the loop, and reputation data that feeds trust signals back to the foundation model companies routing purchases. It sounds straightforward. For most retailers sitting on years of technical debt, it isn't.

The Target conversation goes deeper than store count. Ross argues that physical stores in the AI era aren't just retail locations, they're data collection infrastructure. The in-store experience becomes the top of a data flywheel that fuels ad targeting, brand loyalty, and fulfillment optimization. The risk for any retailer that goes all-in on agentic commerce without protecting that flywheel? Becoming a fulfillment center for someone else's platform.

The episode also tackles the harder strategic question: what happens to the customer relationship when AI agents become the primary interface between buyer and brand? Who owns that relationship? The retailer, or the foundation model company routing the purchase? 

About the hosts

Ross Katz brings a background in analytics and data strategy, working with companies to cut through the noise and focus on what actually drives business value. With experience spanning industries such as e-commerce, education, biotech, and finance, as well as the evolving landscape of AI-enabled work, he focuses on the intersection of data capabilities and business outcomes. He's particularly interested in how shifts in technology change not just what's possible, but how people think about and use data in their daily work.

Jason Bradwell is a seasoned B2B marketing leader, founder of B2B Better and host Pipe Dream, where he explores how modern B2B companies can build media and marketing strategies that drive real revenue and audience growth. 

Connect with us: 

]]> The Back End Is the New Storefront: What AI Agents Mean for Retail Data Strategy The Back End Is the New Storefront: What AI Agents Mean for Retail Data Strategy 00:40:22 683277d8-6b19-4094-a12e-f4c81daf77e8 5 2 full false https://www.corrdyn.com/ Thu, 26 Mar 2026 17:00:36 +0000 Every week brings another AI announcement, another data center project, another promise about what's possible with enough compute. But there's a constraint most people in tech aren't talking about yet - power.

In this episode of Eventual Consistency, Ross Katz sits down with Mickey Peters, former energy executive and Vistage Chair, who spent decades running major power operations across South America for Duke Energy, managing over $1 billion in capital employed. 

The conversation starts with two converging stories: hyperscalers like Meta, Google, and Microsoft building private power generation to bypass grid constraints - one West Texas project consuming more electricity than all of Chicago - and cities like Denver hitting pause on data center development altogether. The bottleneck isn't capital. It isn't technology. It's whether the electricity exists where you need it, and whether communities will let you build there.

Ross and Mickey break down how the major cloud players are each taking radically different approaches to solving the energy problem, from Meta's gas-powered megacampus in Louisiana, to Google's acquisition of an in-house renewable energy developer, to Microsoft reactivating Three Mile Island. They dig into why there's no one-size-fits-all solution, and what the real trade-offs look like between partnering with local utilities versus going behind the meter with your own generation.

But the most underappreciated challenge isn't technical, it's human. Mickey draws on his experience managing energy infrastructure in remote Andean communities to explain why community trust is ultimately what makes or breaks a data center project. He unpacks what those conversations between hyperscalers, local regulators, utilities, and communities actually look like, why NIMBYism is more nuanced than a single objection, and what companies consistently get wrong when they show up to make their case.

About the hosts

Ross Katz brings a background in analytics and data strategy, working with companies to cut through the noise and focus on what actually drives business value. With experience spanning industries such as e-commerce, education, biotech, and finance, as well as the evolving landscape of AI-enabled work, he focuses on the intersection of data capabilities and business outcomes. He's particularly interested in how shifts in technology change not just what's possible, but how people think about and use data in their daily work.

Mickey Peters is an entrepreneur and executive coach who helps leaders build stronger teams, make better decisions, and grow profitability through his Houston Vistage peer advisory group. He brings decades of international leadership experience, including 20+ years living and working in Latin America, and senior roles at Duke Energy.

Connect with us: 

Connect with Mickey Peters LinkedIn

]]> Power Before Code: The Energy Constraints Reshaping AI Infrastructure Power Before Code: The Energy Constraints Reshaping AI Infrastructure 00:39:26 4fd2c09e-2a4c-42e5-bdff-73a865c25b03 4 2 full false https://www.corrdyn.com/ Fri, 06 Mar 2026 18:00:25 +0000 Nearly $300 billion in market value vanished from software companies in a single week after Anthropic’s AI agent launch reignited fears of a “SaaSpocalypse”. In this episode of Eventual Consistency, guest host Jason Bradwell turns the tables and interviews Ross Katz about what’s really happening beneath the headlines. Is AI truly threatening the seat-based SaaS model, or is this another cycle of hype? Ross breaks down the difference between market panic and operational reality, introduces eight key factors that determine which SaaS companies are vulnerable (or defensible), and explains why data gravity, regulatory moats, and revenue model alignment matter more than ever. The conversation explores how AI agents shift the build vs. buy equation, why consumption-based pricing is on the rise, and what data leaders should prioritize in 2026 and beyond. The verdict? AI won’t kill SaaS, but it will reshape it, creating clear winners and losers in the years ahead.

About the hosts

Ross Katz brings a background in analytics and data strategy, working with companies to cut through the noise and focus on what actually drives business value. With experience spanning industries such as e-commerce, education, biotech, and finance, as well as the evolving landscape of AI-enabled work, he focuses on the intersection of data capabilities and business outcomes. He's particularly interested in how shifts in technology change not just what's possible, but how people think about and use data in their daily work.

Jason Bradwell is a seasoned B2B marketing leader, founder of B2B Better and host Pipe Dream, where he explores how modern B2B companies can build media and marketing strategies that drive real revenue and audience growth. 

Connect with us: 

]]> 8 Ways to Survive the SaaSpocalypse 8 Ways to Survive the SaaSpocalypse 00:27:45 0b2123b1-cf08-4f6d-be31-03fd1548818a 3 2 full false https://www.corrdyn.com/ Fri, 20 Feb 2026 18:00:25 +0000 The era of AI experimentation without accountability is over. Following Davos 2025, where business leaders declared the end of pilot-purgatory after $1.5 trillion in AI investments, we dig into what "AI ROI" actually means for data teams. Matt Sekac from Welocalize shares how they have moved beyond demos to production AI across translation workflows, product development, and internal operations, and why the measurement challenges are more nuanced than boardroom proclamations suggest. We explore the tension between needing disciplined experimentation and executives demanding immediate returns, why live data infrastructure matters more than the models themselves, and how AI value shows up in ways beyond cost reduction. 

About the host

Ross Katz brings a background in analytics and data strategy, working with companies to cut through the noise and focus on what actually drives business value. With experience spanning industries such as e-commerce, education, biotech, and finance, as well as the evolving landscape of AI-enabled work, he focuses on the intersection of data capabilities and business outcomes. He's particularly interested in how shifts in technology change not just what's possible, but how people think about and use data in their daily work.

About the guest

Matt Sekac leads R&D, the Data Office, and Data Analytics at Welocalize, where he focuses on building data-driven systems and capabilities that improve decision-making, forecasting, and commercial performance across the business. With a career that blends strategy, analytics, and operational execution, Matthew is known for turning complex data into practical tools, models, and workflows that teams can actually use.

Connect with us: 

Connect with Matt Sekac LinkedIn

]]> “AI's Experimentation Era is Over” Says Davos “AI's Experimentation Era is Over” Says Davos 00:46:07 6b7b3102-af63-49fd-bc43-123f421b3af7 2 2 full false https://www.corrdyn.com/ Thu, 05 Feb 2026 18:00:30 +0000 IBM is acquiring Confluent for $11 billion, and the data world is trying to figure out what it means.

We cut through the press releases and LinkedIn hot takes to discuss what's actually happening here. Is this about mainframe modernization, hybrid cloud expansion, or IBM's bet on AI agents driving streaming adoption?

We examine why IBM paid a 34% premium, what this means for the future of open-source Kafka, and whether the agentic commerce narrative holds water.

Plus, we dig into what data leaders should actually be paying attention to as the industry consolidates around a few major platforms.

About the hosts

James is a data consultant who has spent years in the trenches helping enterprise organizations actually implement the technologies that vendors promise will revolutionize their business. He specializes in data infrastructure, real-time systems, and the practical realities of what works when the proof of concept becomes production. His approach is skeptical, pragmatic, and focused on the economics of technology decisions, because someone has to pay for all that streaming infrastructure.

Ross brings a background in analytics and data strategy, working with companies to cut through the noise and focus on what actually drives business value. With experience spanning industries such as e-commerce, education, biotech, and finance, as well as the evolving landscape of AI-enabled work, he focuses on the intersection of data capabilities and business outcomes. He's particularly interested in how shifts in technology change not just what's possible, but how people think about and use data in their daily work.

Connect with us: 

]]> IBM Buys Confluent: The $11B Bet on Streaming's AI Future IBM Buys Confluent: The $11B Bet on Streaming's AI Future 00:30:36 e003ceba-3dfe-4d0b-bd44-13d8053bc7a3 CorrDyn 1 2 full false https://pod.co/data-bs/ibm-buys-confluent-the-11b-bet-on-streamings-ai-future Thu, 22 Jan 2026 16:11:31 +0000 In this episode of Data BS, host James Winegar and Toby Mao, CTO and co-founder of Tobiko Data, discuss the development of SQL Mesh, insights from Toby’s experiences at Netflix and Airbnb exploring the innovative features of SQL Mesh, and the ability to promote data transformations to production seamlessly.

Join us for a great conversation about how Toby co-founded his company and what’s next for the future in SQL Mesh.

  • Introduction to Tobiko and SQL Mesh
  • Virtual Data Environments and Instant Deployments
  • Introduction to SQL Mesh and CI/CD Integration
  • SQL Glot: Standardizing SQL Across Platforms
  • Type Annotations and Logical Planning in SQL Glot
  • Future Developments and Multi-Gateway Features in SQL Mesh

Connect with Toby Mao on LinkedIn

This podcast is sponsored by CorrDyn

]]> Enhancing Developer Efficiency with SQL Mesh | Featuring Toby Mao Enhancing Developer Efficiency with SQL Mesh | Featuring Toby Mao 00:38:28 ec3419a8-d6c5-4de8-a3ad-d6e85e1e0206 13 1 full false https://www.corrdyn.com/ Wed, 26 Feb 2025 18:00:23 +0000 In this episode of Data BS, James Winegar sits down with Nicole Radziwil, Co-Founder & Chief Data/AI Officer at Qzuku, to dive into the intersection of data, strategy, culture, and power within organizations. They discuss the crucial role of data teams in shaping decision-making, fostering alignment, and navigating power dynamics. Nicole shares valuable insights on how data professionals can drive impact beyond technical execution by facilitating shared understanding across teams.

They also explore the importance of process improvement, visibility, and leadership in data-driven organizations—highlighting how Chief Data Officers (CDOs) and data teams can enhance collaboration and break down silos. Plus, Nicole introduces key concepts from her book Data, Strategy, Culture, and Power and shares actionable steps for organizations to address these challenges.

  • Data teams have unique visibility into organizational misalignments and power dynamics. They should play an active role in resolving these tensions.
  • Improving processes leads to better data and decision-making. Strong processes help teams align on shared goals.
  • A CDO's job isn't just about technology—it’s about enabling the organization to access and use data effectively to drive meaningful change.
  • Data teams should proactively surface misalignments between departments (e.g., sales and marketing) to create shared understanding.
  • Whether in product analytics or broader data strategy, intentional problem-solving leads to scalable and effective solutions.
  • Recognizing and addressing power imbalances in decision-making can help organizations unlock the full potential of their data.
  • Organizational challenges are often rooted in human factors—improving communication, expectations, and feedback loops can significantly enhance productivity.

Resources Mentioned

  • Data, Strategy, Culture, and Power – Nicole Radziwill’s book on data leadership and organizational alignment.
  • People and Data – A book by Tom Redman exploring the human side of data.
  • Force Field Analysis – A technique for analyzing the forces that drive or hinder change in an organization

Connect with Nicole Radziwill on LinkedIn

]]> People as Both the Problem and the Solution in Data | Featuring Nicole Radziwill People as Both the Problem and the Solution in Data | Featuring Nicole Radziwill 00:39:04 5796cc63-abdb-4e70-8fab-8f7e3269e693 12 1 full false https://www.corrdyn.com/ Thu, 13 Feb 2025 18:00:22 +0000 In today’s episode, James Winegar from Corrdyn and Alex Monahan, a Customer Engineer at MotherDuck discuss DuckDB, a powerful analytical database designed for performance and ease of use. They explore the unique features of DuckDB, its relationship with MotherDuck and DuckDB Labs, and the upcoming DuckDB 1.2 release, which promises significant performance improvements. 

The discussion also covers how DuckDB handles out-of-memory datasets, its various use cases, its limitations in certain scenarios, and the importance of extensions, emphasizing DuckDB's ease of use and performance.

  • DuckDB is designed for analytics, making it unique compared to other databases and 1.2 focuses on real-world performance improvements.
  • Proprietary solutions are losing value compared to open-source options.
  • Mother Duck enhances DuckDB for cloud applications and data warehousing.
  • The serverless model at Mother Duck allows for efficient resource usage.
  • Contributing to DuckDB can be done through community extensions and GitHub discussions.

Connect with Alex Monahan on LinkedIn

]]> DuckDB: A Game Changer in Data Analytics | Featuring Alex Monahan DuckDB: A Game Changer in Data Analytics | Featuring Alex Monahan 00:39:40 eea5a348-55f8-4c2b-9d95-16bd794e06e6 11 1 full false https://www.corrdyn.com/ Wed, 29 Jan 2025 18:00:22 +0000 In this episode, Lindsay Murphy, a Head of Data at Hiive and host of the Women Lead Data podcast, joins James Winegar to share her unique journey in the data industry, offering insights on building data-driven strategies, creating balanced teams, and fostering authentic connections. 

From leveraging LinkedIn to understanding the strategic value of data, Lindsay breaks down practical advice for professionals looking to thrive in the evolving world of data.

Key Takeaways:

  • Building Balanced Teams: Lindsay emphasizes the importance of creating diverse and inclusive data teams, discussing her proactive approach to sourcing talent, especially women, on LinkedIn.
  • LinkedIn Optimization: Tips for making your LinkedIn profile recruiter-friendly, including the importance of authenticity and strategic keyword placement.
  • Networking in a Post-COVID World: How virtual coffee chats and remote connections are transforming professional relationships and making networking more accessible.
  • Data as a Strategic Function: The significance of aligning data initiatives with business goals and focusing on ROI to avoid inefficiencies and cuts.
  • Empowering Teams with Self-Serve Models: How self-service tools and well-structured data models can enable smaller teams to deliver outsized value.

Sponsor: CorrDyn, a data consultancy

Connect with Lindsay Murphy on LinkedIn 

Podcast: Women Lead Data on Apple Podcasts | Women Lead Data on Spotify

Mentioned in the episode: Data and AI Diversity Report

]]> From Pipelines to People: Building Strategic and Balanced Data Teams From Pipelines to People: Building Strategic and Balanced Data Teams 00:40:31 4a7936c0-2efe-466a-ae02-9e0b071b8680 10 1 full false https://www.corrdyn.com/ Wed, 15 Jan 2025 18:00:22 +0000 In this episode of Data BS, James Winegar sits down with Matt Barlow, a Cloud Infrastructure Lead from StratusGrid, to explore the transformative potential of generative AI in incident response, platform modernization, and cloud engineering workflows. They dive into practical use cases, discuss the challenges of integrating Gen AI tools into workflows, and address the implications for junior engineers.

From building customizable AI agents to leveraging tools like Cloud Engineer, Matt shares actionable insights on how to enhance productivity while avoiding common pitfalls. This episode is a must-listen for cloud professionals looking to stay ahead of the curve in an evolving tech landscape.

If you enjoyed this episode, don’t forget to subscribe to Data BS wherever you listen to podcasts.

Connect with Our Guest:

]]> Exploring Gen AI in Incident Response and Cloud Engineering | Featuring Matt Barlow from StratusGrid Exploring Gen AI in Incident Response and Cloud Engineering | Featuring Matt Barlow from StratusGrid 00:24:40 928ec657-1a44-4da4-b827-93941f4d6d14 9 1 full false https://www.corrdyn.com/ Thu, 02 Jan 2025 18:00:28 +0000 In this episode of Data BS, host James Winegar, CEO of CorrDyn, sits down with David Yaffe, Co-Founder of Estuary, to explore how their innovative approach to real-time data streaming is revolutionizing data pipelines. David shares how Estuary optimizes efficiency by leveraging streaming architectures, minimizing costs, and prioritizing smart resource allocation.

They also discuss the importance of fostering a responsive customer support culture, Estuary's strategies for handling massive data scenarios, and how thoughtful engineering can create scalable solutions. Whether you're curious about streaming technology or building cost-effective infrastructure, this episode is packed with insights.

Highlights:

  • How Estuary designed connectors to run on just 1 CPU and 1GB RAM.
  • The advantages of streaming-first data processing.
  • Tips on minimizing cloud egress and compute costs.
  • Creating a customer-first engineering culture with real-time Slack support.

Links and resources:

]]> Efficient Data Streaming | Featuring David Yaffe, Estuary Efficient Data Streaming | Featuring David Yaffe, Estuary 00:32:03 ac1b26a0-5127-4161-9e86-7d8137417315 CorrDyn 8 1 full false https://www.corrdyn.com/ Wed, 18 Dec 2024 18:00:27 +0000 Listen to Part One of our interview with Kevin here wherever you get your podcasts - or find a link at the bottom of the Show Notes.

***

In part two of this episode, we continue our conversation with Kevin Hartman, Head of Partner Solutions Architects in the Americas at Databricks and Lecturer at UC Berkeley. A visionary in the tech and data space, Kevin shares how his work at Databricks exemplifies collaboration across industries, academia, and diverse disciplines. From open-source technology to fostering grassroots initiatives like the LMOps program, Kevin emphasizes that sustainable solutions come from a commitment to openness and shared innovation.

Highlighting the vibrant culture at Databricks where passion and innovation go hand in hand, the company has evolved from pioneering Apache Spark to introducing cutting-edge technologies like the Photon engine, Delta Lake, and MLflow. Breaking down silos—whether in data or among people—has been central to their success, enabling an exchange of ideas that fuels continuous improvement. Tune in to explore Kevin’s philosophy, Databricks’ journey, and how open-source principles are shaping the future of data science.

Links and resources:

]]> Building Ethical Data Practices in Cross-Functional Communities | Featuring Kevin Hartman, Databricks - Part 2 Building Ethical Data Practices in Cross-Functional Communities | Featuring Kevin Hartman, Databricks - Part 2 00:29:23 2e8b766a-eb85-4885-9c37-1f92f0c3e070 CorrDyn 7 1 full false https://www.corrdyn.com/ Wed, 04 Dec 2024 18:00:26 +0000 In part one of this episode, we dive deep into the world of open standards, responsible data science, and the transformative power of community with Kevin Hartman, Head of Partner Solutions Architects in the Americas at Databricks and Lecturer at UC Berkeley.

Kevin shares how his work at Databricks exemplifies collaboration across industries, academia, and diverse disciplines. From open-source technology to fostering grassroots initiatives like the LM Ops program, Kevin emphasizes that sustainable solutions come from a commitment to openness and shared innovation. He also advocates for responsible data science practices, encouraging professionals to consider not only what can be built but what should be built, with ethics and accountability at the forefront.

Links and resources:

]]> Building Ethical Data Practices in Cross-Functional Communities | Featuring Kevin Hartman, Databricks - Part 1 Building Ethical Data Practices in Cross-Functional Communities | Featuring Kevin Hartman, Databricks - Part 1 00:27:59 6cf68bf7-5685-411a-a7b9-5ab9af880ed2 CorrDyn 6 1 full false https://www.corrdyn.com Mon, 25 Nov 2024 20:12:19 +0000 In this episode of Data BS, host James Winegar, CEO of CorrDyn, talks with Tino Tereshko, Co-Founder of MotherDuck, about how the value proposition of serverless analytics data warehouses means analytics can now take place anywhere. 

An open-source project that provides fast and efficient data analysis, MotherDuck can create a seamless experience for organizations who are looking for a simple, cost-effective, and easy-to-use data warehouse solution. Tino shares how and why they founded MotherDuck and how the system can adapt when they need to adopt new ideas in the industry. 

Focusing on fairness and efficiency, Tino and James discuss how MotherDuck came to be, their rapid improvements since starting, and scaling as they grow. So say goodbye to lag and hello to zero-millisecond latency as you listen to the latest episode of Data BS from CorrDyn.

Links and resources:

]]> Creating a Serverless Analytics Data Warehouse | Featuring Tino Tereshko Creating a Serverless Analytics Data Warehouse | Featuring Tino Tereshko 00:42:56 5576d1bd-b911-431c-b570-e7150b2f6720 CorrDyn 5 1 full false https://www.corrdyn.com/ Thu, 07 Nov 2024 14:29:37 +0000 In this episode of Data BS, host James Winegar, CEO of CorrDyn, sits down with Sam Kahn, VP of AI and Data Science at TICKR, to dig into the company's focus on AI and data science solutions for the consumer packaged goods sector - one of the fastest moving and most reliant industries on utilizing data to drive decision-making.

Sam shares his insights into the unique challenges CPG companies face in taking control of their data, the role of GenAI in enhancing forecasting and data categorization, and the importance of data cleansing and to streamline business operations. The pair also unpack novel use cases for GenAI, including survey response prediction and proactive business decision-making based on consumer sentiment. 

James then asks Sam to discuss the intricacies of out-of-stock prediction accuracy, some of the biggest challenges CPG organizations face around getting control of their data, and the role of generative AI in automating business processes - now, and into the future. 

Finally, they round out the conversation by exploring how TICKR’s solutions can enhance operational efficiency and forecasting capabilities for CPG companies. 

Links & Resources:

]]> Transforming CPG with AI | Featuring Sam Kahn, TICKR Transforming CPG with AI | Featuring Sam Kahn, TICKR 00:34:03 60fd5a9f-3c93-4e7b-a703-a79fd63671ef CorrDyn 4 1 full false https://www.corrdyn.com/ Wed, 23 Oct 2024 14:56:20 +0000 In this episode of Data BS, host James Winegar, CEO of CorrDyn, sits down with Carlos Aguilar, founder of Hashboard, to dive deep into the world of semantic business intelligence and explore how it transforms data management across organizations.

Carlos explains how Hashboard is changing the way companies handle their metrics, offering a centralized system for managing and exploring data.

He shares how Hashboard solves the problem of multiple sources of truth and eliminates the complexities of outdated dashboards, giving users—both technical and non-technical—the tools they need to access and interrogate their own data.

Carlos provides insight into Hashboard’s “Explore” feature and how it empowers users to answer business-critical questions without needing to write code. Then, he and James also discuss Hashboard’s approach to version control and governance.

Finally, Carlos reveals Hashboard’s vision for scaling up, from supporting small startups to mid-market and even large enterprise organizations.

Links & Resources:

]]> Unlocking the Power of Semantic BI | Featuring Carlos Aguilar, Hashboard Unlocking the Power of Semantic BI | Featuring Carlos Aguilar, Hashboard 00:32:46 1236d490-ab94-46fc-9d7b-ba84a7bbc436 CorrDyn 3 1 full false https://www.corrdyn.com/ Wed, 09 Oct 2024 08:54:44 +0000 In this episode of Data BS, host James Winegar, CEO of CorrDyn, sits down with Jamil Bou Kheir, founder of Firezone, to explore the evolving landscape of Zero Trust Network Access and its growing impact on data security.

Jamil shares how Firezone stands out from traditional VPN solutions, offering businesses a more secure, fine-tuned approach to protecting their networks and sensitive data.

Drawing from his experience at Cisco during the pandemic, Jamil discusses the challenges of scaling remote work security and how Firezone’s architecture is designed to handle these issues.

The conversation then turns to how Firezone helps businesses protect their databases from data breaches and the steps organizations can take to overcome the complexity of modern security frameworks.

Jamil also gives some insight into Firezone’s upcoming roadmap and how the company is positioned to support both SMBs and large enterprises.

Links & Resources:

]]> Exploring Zero Trust Security | Featuring Jamil Bou Kheir, Firezone Exploring Zero Trust Security | Featuring Jamil Bou Kheir, Firezone 00:31:42 9211f1b8-0bdd-4e32-a782-7a6f76353f08 CorrDyn 2 1 full false https://www.corrdyn.com/ Wed, 09 Oct 2024 08:54:35 +0000 In this episode of Data BS, host James Winegar, CEO of CorrDyn, sits down with Sam Arnold, an enterprise account executive at Census, a leading data activation and reverse ETL platform.

Sam shares his journey into the data space and provides insights into how Census differentiates itself in a competitive market.

With James, the pair dig into the power of reverse ETL, the limitations of traditional customer data platforms, and how Census enables non-technical teams, like marketing and product, to use data without constantly needing help from data engineers.

The conversation also dives deep into how AI tools like ChatGPT and Claude are transforming the sales profession. Sam explains how AI-driven engagment fit scores and productivity enhancements have helped his team streamline their workflow and increase efficiency.

The episode finishes up with a discussion on the future of AI in business, from drug discovery to manufacturing, and how AI will continue to revolutionize industries.

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]]> Maximizing Sales Efficiency with AI and Data Activation Tools | Featuring Sam Arnold, Census Maximizing Sales Efficiency with AI and Data Activation Tools | Featuring Sam Arnold, Census 00:32:06 af796428-a9e5-4802-8658-97ccad42af83 CorrDyn 1 1 full false https://www.corrdyn.com/ Mon, 07 Oct 2024 20:36:32 +0000