Data Engineering Podcast
A podcast by Tobias Macey - Sundays
Categories:
419 Episodes
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Leveraging Human Intelligence For Better AI At Alegion With Cheryl Martin - Episode 38
Published: 2/07/2018 -
Package Management And Distribution For Your Data Using Quilt with Kevin Moore - Episode 37
Published: 25/06/2018 -
User Analytics In Depth At Heap with Dan Robinson - Episode 36
Published: 17/06/2018 -
CockroachDB In Depth with Peter Mattis - Episode 35
Published: 11/06/2018 -
ArangoDB: Fast, Scalable, and Multi-Model Data Storage with Jan Steeman and Jan Stücke - Episode 34
Published: 4/06/2018 -
The Alooma Data Pipeline With CTO Yair Weinberger - Episode 33
Published: 28/05/2018 -
PrestoDB and Starburst Data with Kamil Bajda-Pawlikowski - Episode 32
Published: 21/05/2018 -
Brief Conversations From The Open Data Science Conference: Part 2 - Episode 31
Published: 14/05/2018 -
Brief Conversations From The Open Data Science Conference: Part 1 - Episode 30
Published: 7/05/2018 -
Metabase Self Service Business Intelligence with Sameer Al-Sakran - Episode 29
Published: 30/04/2018 -
Octopai: Metadata Management for Better Business Intelligence with Amnon Drori - Episode 28
Published: 23/04/2018 -
Data Engineering Weekly with Joe Crobak - Episode 27
Published: 15/04/2018 -
Defining DataOps with Chris Bergh - Episode 26
Published: 8/04/2018 -
ThreatStack: Data Driven Cloud Security with Pete Cheslock and Patrick Cable - Episode 25
Published: 1/04/2018 -
MarketStore: Managing Timeseries Financial Data with Hitoshi Harada and Christopher Ryan - Episode 24
Published: 25/03/2018 -
Stretching The Elastic Stack with Philipp Krenn - Episode 23
Published: 19/03/2018 -
Database Refactoring Patterns with Pramod Sadalage - Episode 22
Published: 12/03/2018 -
The Future Data Economy with Roger Chen - Episode 21
Published: 5/03/2018 -
Honeycomb Data Infrastructure with Sam Stokes - Episode 20
Published: 26/02/2018 -
Data Teams with Will McGinnis - Episode 19
Published: 19/02/2018
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.