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

“What is a data mesh?” It’s one of the most frequently asked questions on this podcast, and is almost a microcosm for data and analytics as a whole. It may be the next big thing. It may be yet another passing fad in architectural design. We compared and contrasted it with data fabric in Episode 32 and spoke with Zhamak Dehghani, the founder of the data mesh paradigm in Episode 44. We even hosted a special panel discussion dedicated to data mesh. After all these discussions, we are still trying to figure out what it is. So, we’re settling this the only way we know how: a good old-fashioned debate. Only one side can win. This episode will feature: The definitive(ish) definition of data mesh A look at why organizations struggle to understand and implement it What is your data “hot take” that everyone else disagrees with?

When we think about good, responsible data stewardship, we often think in terms of compliance and governance. We talk about access, trust, and consumption. But there’s another dimension we must consider if we’re to be truly responsible with data. We simply can’t ignore the role of ethics in data use. Join Tim, Juan and special guest Partha Srinivasa, award-winning CIO/CTO/CDO and current CDO of Verisk, for a conversation about data responsibility and ethics. This episode will feature: Common misperceptions about data and ethics How to build ethics into your data practice Can you be both ethical and a fan of the morally dubious, Seinfeld?

Quick, what’s the difference between a data engineer and a data analyst? One preps the data, the other analyzes the data, right? A data scientist, meanwhile, analyzes more complex and disorganized data. The truth is all three of these roles perform overlapping functions leading to an incredible amount of confusion in the job market. Join Tim, Juan and special guest Danielle Oberdier, founder of DiKayo Data and host of the popular DataFemme podcast, to talk about the state of data jobs. How do we make sense of the roles that are out there today, who should companies be looking for in their hiring process, and what new and exciting data positions are starting to emerge? This episode will feature: Certifications that make you more marketable How to stand among your peers in a crowded job market What was the very first job you ever had?

Is your data infrastructure designed for the next decade of data work? Probably not, but are you at least heading in the right direction? It’s an existential question that often reveals fundamental flaws in the system. Join Tim, Juan and special guest Mammad Zadeh, former VP of Engineering at Intuit, for a deep dive on data tools, leadership, and change management. This episode will feature: A look at the rocky road ahead for CDOs How to effectively scale data teams What's your crisis comfort food?

Fall summit 2021 is right around the corner!!!! Join speakers from Nationwide, ThoughtSpot and MANY MORE to discuss hot topics like Data Mesh, DataOps, and the future of data management on Sep. 29: data.world/events/summit ________________ With the hype of graph databases and knowledge graphs, a common (mis)practice is to quickly migrate your existing siloed data into a graph database. But be careful! You may just be bringing the complexity of your silos into the graph. Join Tim, Juan and guest Jans Aasman from Franz Inc, the makers of AllegroGraph, for a conversation on why your graph-based machine learning and 360 projects should start with data modeling. This episode will feature: Data modeling approaches you should consider Tips to avoid data modeling pitfalls Juan and Tim striking their best model pose

Don't forget to register for the data.world Fall summit 2021: data.world/events We all strive to be data-driven. And yet we all instinctively know that we’re not very good at it. In fact, if you believe any number of recent surveys, it seems we may actually be getting worse at data. One reason for this is a misalignment on what success looks like. How do you define and measure it? What is the actual value of your data? This week, Tim and Juan join Lars Albertsson, founder of Scling, to talk about data productivity and balancing a technology vs product-driven approach to data. This episode will feature: Companies that have truly unlocked data value and how they did it Common missteps along the data maturity journey What have you been practicing... but not actually getting any better at?

ETL (Extract Transform and Load) was the SOP for data integration for 25+ years. A decade ago the introduction of data lakes pushed transformation to the end of the process and into tools like Snowflake, BigQuery, and Redshift. Now the latest chatter in the data management industry is Reverse ETL. Shouldn’t we call this LTE? Join Tim, Juan and special guest Tejas Manohar, CEO of Hightouch for a conversation about Reverse ETL and why it matters now. This episode will feature: The evolution of data integration pipelines Use cases for Reverse ETL What other acronyms make you smh?

You can’t get from your home to the grocery simply by owning a car. You have to actually drive the vehicle to get to a place that delivers value. Sounds obvious right? But we don’t instinctively think this way when it comes to data. We focus so much on tools, processes, and architectures, but we don’t talk enough about actually using the data. This week, Tim and Juan are joined by Mike Ferguson, managing director of Intelligent Business Strategies Limited to look at why we’re not using data nearly as effectively as we think and what can be done about it. This episode will feature: Data usage do’s and don’ts How to get your company aligned on effective data use and measurement? What’s the most expensive thing you bought that you’ve never used?

We all want to get more value from our data, right? So should we wrangle it, prep it, classify it, mine it, or model it? Then once we’ve got our data squared away, should we do prescriptive or predictive analytics? And does that require real-time or just-in-time data? If we had a nickel for every buzzword we hear, we could afford far better podcasting equipment. In this episode, Tim and Juan are joined by Kirk Borne, Chief Science Officer at Dataprime AI to demystify some of our most egregious buzzwords and look at what everyone’s going to be talking about next. This episode will feature: What is industry 4.0? How can an edge be intelligent? What is the buzzword that makes you want to pull your hair out the most?

Open source software is one of the largest and fastest growing segments within the data landscape. And if you’re implementing DataOps practices or considering data mesh, openness and flexibility are key architectural principles. This week, Juan and Tim are joined by Denise Gosnell, CDO of Datastax, to talk about the business of open source and how community-centric data applications are reshaping the enterprise. This episode will feature: A glimpse into the future of open source data The difference between open source and open core What open source tool best personifies your personality?