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

The 2026 dbt Labs State of Analytics Engineering report surveyed 363 data practitioners (not vendors, not analysts, but the people building and maintaining data systems). The headline finding is a tension that most people working in or alongside data teams will recognise immediately: AI is now embedded in daily data work, teams are shipping more and faster, and yet trust as a stated priority jumped from 66% to 83% in a single year. At the same time, 41% of respondents still report ambiguous data ownership, 53% still cite poor data quality, and compute costs are up 50% while only 36% of teams report rising budgets. The report calls it "acceleration without stabilization." In this episode of Eventual Consistency, we use the report as a lens on a bigger question: what is AI actually doing to the relationship between data teams and the rest of the business? Ross Katz from CorrDyn, works with organizations across multiple industries as part of their external data team, offering a vantage point that most internal practitioners don't have. He unpacks why the bottleneck in most data organisations has shifted from infrastructure to accountability, and why the real challenge isn't technical. It's political. Key topics covered >> "Acceleration without stabilization": what it looks like inside organizations and why data teams bear the cost of the gap >> Why the biggest constraint in the AI era isn't time or money, it's attention >> Stakeholder management as a data team survival skill: how to navigate upward in environments that prioritise speed over foundations >> The four layers of data work; generation, integration, maintenance, governance and where AI actually helps vs. creates new demand >> The budget squeeze: compute costs up 50%, team budgets up 36% and what that asymmetry forces data teams to deprioritise >> Trust as infrastructure: when it matters most, where it can be traded off, and what dbt's framing gets right and oversimplifies >> From enablement layer to control layer: how the data team's role is shifting as AI agents enable end-runs around traditional data infrastructure >> The distinction between summarization and synthesis and why it matters for anyone building an organisational knowledge base for AI 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 hosts 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: Sponsor: CorrDyn, a data consultancyConnect with Ross Katz on LinkedInConnect with Jason Bradwell LinkedIn

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: Sponsor: CorrDyn, a data consultancyConnect with Ross Katz on LinkedInConnect with James Winegar on LinkedIn

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: Sponsor: CorrDyn, a data consultancyConnect with Ross Katz on LinkedIn Connect with Mickey Peters LinkedIn

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: Sponsor: CorrDyn, a data consultancyConnect with Ross Katz on LinkedIn Connect with Matt Sekac LinkedIn

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 MeshVirtual Data Environments and Instant DeploymentsIntroduction to SQL Mesh and CI/CD IntegrationSQL Glot: Standardizing SQL Across PlatformsType Annotations and Logical Planning in SQL GlotFuture Developments and Multi-Gateway Features in SQL Mesh Connect with Toby Mao on LinkedIn This podcast is sponsored by CorrDyn

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

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: Matt Barlow on GitHub: github.com/MattBarlow-SGConnect with Matt Barlow on LinkedIn Sponsor: CorrDyn, a data consultancy

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: Link to Part One. Connect with Kevin Hartman on LinkedInSponsor: CorrDyn, a data consultancy

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: Connect with Tino Tereshko’s on LinkedInSponsor: CorrDyn, a data consultancy

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: Connect with Carlos Aguilar on LinkedInSponsor: CorrDyn, a data consultancy.

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. Links & Resources: Visit Census: getcensus.comConnect with Sam Arnold on LinkedIn: Sam ArnoldSponsor: CorrDyn, a data consultancy.