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 2 hours 51 minutes
Ship Faster With An Opinionated Data Pipeline Framework
An interview about how the open source Kedro framework makes it faster and easier to build your end-to-end data pipeline for machine learning projects
Open Source Object Storage For All Of Your Data
An interview on the open source MinIO platform for fast and flexible object storage for data intensive applications and analytics that runs everywhere
Navigating Boundless Data Streams With The Swim Kernel
An interview about using stateful computation on data streams with the SwimOS kernel to improve your analytics
Building A Reliable And Performant Router For Observability Data
An interview about building the Vector project to unify delivery of logs and metrics for better system observability
Building A Community For Data Professionals at Data Council
An interview with Pete Soderling about building and growing the Data Council events and helping engineers build businesses
Building Tools And Platforms For Data Analytics
An interview on what data engineers need to know about building tools and platforms for data analytics
A High Performance Platform For The Full Big Data Lifecycle
An interview about the HPCC Systems platform, its journey to open source, and how it handle the full lifecycle of big data for enterprise scale analytics
Digging Into Data Replication At Fivetran
An interview about how the Fivetran platform is designed to handle data replication as a service
Solving Data Discovery At Lyft
An interview about the open source Amundsen platform for data discovery and how Lyft is using it to improve their analytics workflow
Simplifying Data Integration Through Eventual Connectivity
An interview about a new pattern for data integration that reduces the amount of effort required to find connections in numerous data sets