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: 16 days 1 hour 56 minutes
Understanding The Immune System With Data At ImmunAI
An interview with Guy Yachdav about the work that he and his team are doing at ImmunAI to help researchers and scientists understand the immune system through data and machine learning.
Build Your Python Data Processing Your Way And Run It Anywhere With Fugue
An interview with Kevin Kho about the open source Fugue framework for abstracting away the execution engine for your Python data workflows so you can write it once and run it anywhere.
Bring Your Code To Your Streaming And Static Data Without Effort With The Deephaven Real Time Query Engine
An interview with Pete Goddard about the impressive engineering that he and his team have put into the Deephaven real time query engine for effortlessly working across streaming and static data in your preferred language.
Build Your Own End To End Customer Data Platform With Rudderstack
An interview with Soumyadeb Mitra about the unique requirements for information processing in a customer data platform and how the open source Rudderstack platform allows you to customize it to meet your needs.
Scale Your Spatial Analysis By Building It In SQL With Syntax Extensions
An interview with Matthew Forrest about using SQL to build your spatial analysis workflows so that they are more maintainable and uniform
Scalable Strategies For Protecting Data Privacy In Your Shared Data Sets
An interview with Privacy Dynamics lead engineer Will Thompson about useful strategies for managing data privacy in your shared data sets.
A Reflection On Learning A Lot More Than 97 Things Every Data Engineer Should Know
An exploration of the macroscopic and microscopic themes and details that are useful for new and experienced data engineers to know in order to grow their careers.
Effective Pandas Patterns For Data Engineering
An interview with Matt Harrison about how to write effective pandas code for scalable and maintainable data processing logic that can be understood by other members of your team.
Building And Managing Data Teams And Data Platforms In Large Organizations With Ashish Mrig
An interview with Ashish Mrig about his career in data engineering, his experiences managing data teams at Wayfair, and the technical considerations that factor into platform design decisions in large organizations.
The Importance Of Data Contracts As The Interface For Data Integration With Abhi Sivasailam
An interview with Abhi Sivasailam about his work at Flexport to design and implement a data mesh solution that relies heavily on data contracts to provide a stable interface that teams can implement for integrating analytical workflows across the organization.