The Data Stack Show
Podcast készítő Rudderstack

Kategóriák:
440 Epizód
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78: The Etymology of Reverse ETL & Why It’s a Key Piece Of The Modern Data Stack with Boris Jabes of Census
Közzétéve: 2022. 03. 09. -
The PRQL: Reverse ETL and the Distinction Between Operation vs Analysis on Data
Közzétéve: 2022. 03. 04. -
77: Standardizing Unstructured Data with Verl Allen of Claravine
Közzétéve: 2022. 03. 02. -
The PRQL: If Everything Is Data, How Can We Make Sense of It All?
Közzétéve: 2022. 02. 25. -
76: Why a Data Team Should Limit Its Own Superpowers with Sean Halliburton of CNN
Közzétéve: 2022. 02. 23. -
The PRQL: How Important Is the Human Factor When Working With Data?
Közzétéve: 2022. 02. 18. -
75: How To Become a Data Engineer with Parham Parvizi of the Data Stack Academy
Közzétéve: 2022. 02. 16. -
The PRQL: Can We Define the Role of the Data Engineer (Yet)?
Közzétéve: 2022. 02. 11. -
74: Kostas Respawns at Starburst, is Interviewed by Eric, and Reminisces About Winamp
Közzétéve: 2022. 02. 09. -
The PRQL: What Prompts a Conversation About Winamp & Quake Arena on The Data Stack Show?
Közzétéve: 2022. 02. 04. -
73: What a High Performing Data Team (and Stack) Looks Like with Paige Berry of Netlify
Közzétéve: 2022. 02. 02. -
The PRQL: How High Performing Data Teams Put Tooling in the Background
Közzétéve: 2022. 01. 28. -
72: Building Data Ops Into the Data Lifecycle with Douwe Maan of Meltano
Közzétéve: 2022. 01. 26. -
The PRQL: Is It Viable to Manage Integrations Open Source?
Közzétéve: 2022. 01. 21. -
71: ETL at the Edges with Jimmy Chan of Dropbase
Közzétéve: 2022. 01. 19. -
The PRQL: Is Kostas an Excel Power User Yes/No?
Közzétéve: 2022. 01. 14. -
70: The Difference Between Data Lakes and Data Warehouses with Vinoth Chandar of Apache Hudi
Közzétéve: 2022. 01. 12. -
The PRQL: What Old Tech Concepts Were Borrowed to Build the Data Lake House?
Közzétéve: 2022. 01. 07. -
69: What is the Modern Data Stack?
Közzétéve: 2022. 01. 05. -
The PRQL: Should Data Trust Drive the Evolution of Your Data Stack?
Közzétéve: 2021. 12. 31.
Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.