Conversations at the intersection of data engineering and business

with Kostas Pardalis & Eric Dodds

Episode 183

March 27, 2024

with Chad Sanderson

 – CEO, Gable.ai

This week on The Data Stack Show, Eric and Kostas chat with Chad Sanderson, the CEO at Gable.ai. During the episode, Chad discusses the complexities of managing the data supply chain, emphasizing the importance of data quality, feedback loops, and aligning incentives within organizations. He shares his journey from analyst to data infrastructure leader at companies like Oracle, Sephora, and Microsoft. Chad introduces his company, Gable, which tackles upstream data quality issues. He critiques traditional data catalogs and advocates for a more dynamic, decentralized approach. The conversation explores the role of metadata, the integration of data quality checks in the software development lifecycle, the need for cultural shifts towards data responsibility, the significance of full lineage graphs and semantic metadata, treating data as a product with quality gates, and more.

Episode 182

March 20, 2024

with Kevin Liu

 – Software Engineer, Stripe

This week on The Data Stack Show, Eric and Kostas chat with Kevin Liu, Software Engineer at Stripe. During the episode, Kevin discusses data infrastructure challenges and the development of data products. He also shares insights on the importance of metadata management and the role of catalogs in maintaining data consistency across various systems. The conversation also covers open-source projects like the Python Iceberg library and the future of databases in the cloud, the ease of use of internal tools, the integration of data for builders, the balance between simplicity and functionality in user interfaces, and more.

Episode 181

March 13, 2024

with Mike Driscoll

 – CEO, Rill Data

This week on The Data Stack Show, Eric and Kostas chat with Mike Driscoll, the CEO of Rill Data. During the episode, Mike recounts his journey from the Human Genome Project to developing the Druid engine, which was created to handle massive advertising data. He discusses Druid’s adoption by major companies and its evolution, emphasizing the importance of speed, simplicity, and scalability in data tools. The dialogue covers the progression of BI tools, the role of object stores, and the integration of AI in data technology. Mike also touches on the significance of SQL and AI’s influence on data visualization, what he would do if he wasn’t working in data, and more.