Keeping Up With Data — Week 16 Reading List

5 minutes for 5 hours’ worth of reading

  • The Future of Data Lineage — Beyond a Diagram: The purpose of data lineage is not to have a nice diagram to look at. The purpose is to solve data engineering problems: What is the impact of this infrastructure change? Why is this dashboard broken? Is anyone using this table? How is this field calculated? Where are the PII data? Having lineage data can help answering these. That’s its true power. (Dan Mashiter @ Alvin)
  • Run Your Data Team Like A Product Team: Solving customers’ needs, not just answering their questions should be the focus of a data team. My product management knowledge is very limited, so I struggled a bit with the product management analogy. However, the practicalities about a data team focusing on their (internal) customers, striving for business impact rather than outputs and the importance of 2-way communication are deeply aligned with my experience. “Data teams should be 3–10% of the total headcount,” suggest the authors. But I’m less sure about that. (Locally Optimistic)
  • Don’t hire top talent; hire for weaknesses. I’ve been repeatedly told by recruiters that I’m writing the worse job descriptions. That’s because I don’t want to put an ideal candidate on the paper. First, I’m afraid that I might be wrong (not knowing what I don’t know). And second, I know I won’t find that ideal candidate. I always struggled to explain the ambiguous approach to recruiting that I’m taking — talking to interesting candidates (ignoring the ‘absolutely required’ items in the job ad) and testing how could they help the current team better. This article speaks my mind. (Benji Weber)



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Adam Votava

Data scientist | avid cyclist | amateur pianist (I'm sharing my personal opinion and experience, which should not to be considered professional advice)