Plumbers of Data Science
Podcast készítő Andreas Kretz

Kategóriák:
118 Epizód
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#29 Recruiting is harder than I thought
Közzétéve: 2024. 11. 04. -
#28 Freelancing as a Data Engineer - Hero Talk with the "Seattle Data Guy" Ben Rogojan
Közzétéve: 2024. 10. 25. -
#27 We Are Starting a Recruiting Service!
Közzétéve: 2024. 10. 18. -
#26 Data Modeling is F***ing Easy!
Közzétéve: 2024. 09. 23. -
#25 His Career Started With a Bootcamp & Now He Helps Others Succeed - Hero Talk w/ Mezue Obi-Eyis
Közzétéve: 2024. 09. 20. -
#24 Dirty Data & Data Cleaning - Hero Talk with "The Classification Guru" Susan Walsh
Közzétéve: 2024. 09. 16. -
#23 A Deep Dive Into APIs, IoT, and Data Storage - Hero Talk with Paolo Lulli
Közzétéve: 2024. 09. 09. -
#22 Why testing data pipelines can be so challenging - and how to tackle it
Közzétéve: 2024. 09. 06. -
#21 Is This the Synthetic Data Revolution?! Hero Talk with Mario Scriminaci from Mostly AI
Közzétéve: 2024. 09. 02. -
#20 Bootcamps vs Coaching
Közzétéve: 2024. 08. 30. -
#19 Why your data and goals matter more than tools!
Közzétéve: 2024. 08. 23. -
#18 Why Apache Spark Is Such An Essential Skill - Hero Talk with Philipp Brunenberg
Közzétéve: 2024. 08. 19. -
#17 The Future of Data Observability - Hero Talk with Ryan Yackel
Közzétéve: 2024. 08. 12. -
#16 Should You Move to Germany for a Data Engineering Career?
Közzétéve: 2024. 08. 09. -
#15 Personal Branding in Data - Hero Talk with Kate Strachnyi
Közzétéve: 2024. 08. 05. -
#14 The Secret Why Time Series Databases Are Awesome - Hero Talk with Jeff Tao
Közzétéve: 2024. 08. 02. -
#13 From India to the U.S.: Becoming a Data Engineer at Toyota - Hero Talk with Ayan Tiwari
Közzétéve: 2024. 07. 29. -
#12 Data Tools & Platforms: Why you should always be skeptical
Közzétéve: 2024. 07. 26. -
#11 GenAI from a Data Engineer's perspective - Hero Talk with Vinoth Nageshwaran
Közzétéve: 2024. 07. 22. -
#10 Why Excel should be a go-to tool for data professionals
Közzétéve: 2024. 07. 19.
Data Engineering is the plumbing of data science. Almost invisible, but super important and a big mess when done wrong. We talk about interesting Data Engineering trends and topics. I also train Data Engineering in my Data Engineering Academy at LearnDataEngineering.com