Is It True We Do Development in Data?
summary
The talk examines what people mean by “working in Data” amid the rise of LLMs and AI, contrasting simple data-visualization tasks (e.g., making pie charts) with engineering-style work such as developing codebases in Spark/Scala. It also clarifies roles in the data ecosystem—Data Scientist, Data Engineer, Data Analyst—by drawing on the speaker’s five years of experience on Data/Big Data teams to explore whether those activities count as software development.
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chapters (13)
- 0:00Introduction
- 1:11Data career paths
- 2:21Raw data sources
- 3:07Data replication staging
- 4:57Data transformation warehouse
- 6:47Python Pandas
- 8:56Automation Spark big data
- 9:38Python data visualization
- 10:45Data prep for science
- 12:11Pipeline sharing industrialization
- 12:55Data roles skills
- 15:22Dev best practices
- 16:34Q&A
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