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Evolution and Challenges of Data Team Tooling
The chapter explores the evolution and challenges faced by data teams in terms of tooling and velocity, emphasizing the need for investing in the right tools and benchmarks. It discusses the shift from traditional to modern deployment models, complexities in encoding dependencies, and the debate around choosing the backend stack for data engineering. The conversation reflects on the need for reevaluating infrastructure stacks to meet the unique requirements of data teams and creating a unified language or environment in the data engineering field.