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.
https://www.dataengineeringpodcast.com
Gesamtlänge aller Episoden: 15 days 23 hours 52 minutes
Building Data Pipelines That Run From Source To Analysis And Activation With Hevo Data
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.
Introduce Climate Analytics Into Your Data Platform Without The Heavy Lifting Using Sust Global
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.
A Reflection On Data Observability As It Reaches Broader Adoption
Summary
Data observability is a product category that has seen massive growth and adoption in recent years. Monte Carlo is in the vanguard of companies who have been enabling data teams to observe and understand their complex data systems. In this episode founders Barr Moses and Lior Gavish rejoin the show to reflect on the evolution and adoption of data observability technologies and the capabilities that are being introduced as the broader ecosystem adopts the practices...
An Exploration Of What Data Automation Can Provide To Data Engineers And Ascend's Journey To Make It A Reality
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
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.
An Exploration Of The Expectations, Ecosystem, and Realities Of Real-Time Data Applications
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.
Understanding The Role Of The Chief Data Officer
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
Bringing Automation To Data Labeling For Machine Learning With Watchful
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.
Collecting And Retaining Contextual Metadata For Powerful And Effective Data Discovery
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
Useful Lessons And Repeatable Patterns Learned From Data Mesh Implementations At AgileLab
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.