This show goes behind the scenes for the tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation are just some of the topics that you will find here.
September 25th, 2022 | 41 mins 1 sec
An interview with Tom Baeyens about the Soda Checks Language and how it was designed to express the various concerns involved in data reliability engineering in a format that is approachable by everyone.
Building A Shared Understanding Of Data Assets In A Business Through A Single Pane Of Glass With Workstream
September 18th, 2022 | 54 mins 51 secs
An interview with Nicholas Freund about his efforts at Workstream to build a single view of data assets and their status across the organization in a context that is understandable by everyone.
September 18th, 2022 | 1 hr 32 mins
In this episode Tommy Yionoulis talks about how incorporating deliberate data collection into business processes can drive important operational insights in multi-location businesses and his work at OpsAnalitica to make it manageable.
Build Confidence In Your Data Platform With Schema Compatibility Reports That Span Systems And Domains Using Schemata
September 11th, 2022 | 59 mins 39 secs
An interview with Ananth Packildurai about the Schemata project and how it provides visibility into the connections and compatibility of schemas that flow from source systems through all of your transformations and into your data assets.
September 11th, 2022 | 57 mins 15 secs
An interview with Manish Jethani about the Hevo Data platform for building end-to-end data pipelines that automate flows from source systems, into the warehouse, and out to operational platforms without all of the maintenance overhead.
September 4th, 2022 | 58 mins 39 secs
September 4th, 2022 | 54 mins 18 secs
An interview with Gopal Erinjippurath about Sust Global's work to bring climate analytics into your data platform through robust APIs and curated data sets.
An Exploration Of What Data Automation Can Provide To Data Engineers And Ascend's Journey To Make It A Reality
August 28th, 2022 | 1 hr 3 mins
An interview with Sean Knapp about the potential impact of data automation and the various considerations and capabilities that are required to make it a reality.
Alumni Of AirBnB's Early Years Reflect On What They Learned About Building Data Driven Organizations
August 28th, 2022 | 1 hr 10 mins
An interview with alumni of AirBnB's formative years as a data driven organization about the lessons that they learned there and how they are carrying them forward in the founding of new data companies.
August 21st, 2022 | 1 hr 6 mins
An interview with Shruti Bhat about the state of the ecosystem for real-time data applications and the motivating factors for when and how to build them.
August 21st, 2022 | 47 mins 10 secs
An interview with Tracy Daniels, CDO of Truist, about the role and responsibilities of the Chief Data Officer and when your organization might need one
August 13th, 2022 | 1 hr 20 mins
An interview with Shayan Mohanty about the challenges of building repeatable data labeling processes and how Watchful is building a platform to let domain experts codify their knowledge for automated labeling of training data for machine learning projects.
August 13th, 2022 | 53 mins 24 secs
An interview with Shinji Kim about the challenges of collecting contextual metadata for your information assets and how to organize it to power effective data discovery for everyone in the business
August 6th, 2022 | 48 mins 30 secs
An interview with Paolo Platter about the experience that he and his team at AgileLab have had implementing Data Mesh strategies at multiple organizations and the repeatable patterns that they have built into their Data Mesh Boost product.
August 6th, 2022 | 58 mins 51 secs
An interview with Frank Liu about the open source vector database Milvus and how its native storage of vector embeddings reduces the friction involved in building and deploying machine learning models.
July 31st, 2022 | 40 mins 37 secs
An interview with David Bader about the Arkouda framework for exploratory data analysis at interactive speeds across massive data sets and how it supports operating from a single laptop to multiple servers in the cloud or thousands of cores on a supercomputer