Data Engineering Podcast
A podcast by Tobias Macey - Domenica
Categorie:
419 Episodio
-
Repeatable Patterns For Designing Data Platforms And When To Customize Them
Pubblicato: 03/04/2022 -
Eliminate The Bottlenecks In Your Key/Value Storage With SpeeDB
Pubblicato: 27/03/2022 -
Building A Data Governance Bridge Between Cloud And Datacenters For The Enterprise At Privacera
Pubblicato: 27/03/2022 -
Exploring Incident Management Strategies For Data Teams
Pubblicato: 20/03/2022 -
Accelerate Your Embedded Analytics With Apache Pinot
Pubblicato: 20/03/2022 -
Accelerating Adoption Of The Modern Data Stack At 5X Data
Pubblicato: 14/03/2022 -
Taking A Multidimensional Approach To Data Observability At Acceldata
Pubblicato: 14/03/2022 -
Move Your Database To The Data And Speed Up Your Analytics With DuckDB
Pubblicato: 05/03/2022 -
Developer Friendly Application Persistence That Is Fast And Scalable With HarperDB
Pubblicato: 05/03/2022 -
Reflections On Designing A Data Platform From Scratch
Pubblicato: 28/02/2022 -
Manage Your Unstructured Data Assets Across Cloud And Hybrid Environments With Komprise
Pubblicato: 28/02/2022 -
Build Your Python Data Processing Your Way And Run It Anywhere With Fugue
Pubblicato: 21/02/2022 -
Understanding The Immune System With Data At ImmunAI
Pubblicato: 21/02/2022 -
Bring Your Code To Your Streaming And Static Data Without Effort With The Deephaven Real Time Query Engine
Pubblicato: 14/02/2022 -
Build Your Own End To End Customer Data Platform With Rudderstack
Pubblicato: 14/02/2022 -
Scale Your Spatial Analysis By Building It In SQL With Syntax Extensions
Pubblicato: 07/02/2022 -
Scalable Strategies For Protecting Data Privacy In Your Shared Data Sets
Pubblicato: 06/02/2022 -
A Reflection On Learning A Lot More Than 97 Things Every Data Engineer Should Know
Pubblicato: 31/01/2022 -
Effective Pandas Patterns For Data Engineering
Pubblicato: 31/01/2022 -
The Importance Of Data Contracts As The Interface For Data Integration With Abhi Sivasailam
Pubblicato: 23/01/2022
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.