In the past few years, much has been written about problems like discoverability, observability, data quality, and the need for data teams to become more “engineering oriented” in their mindset. Movements like analytics engineering and open source tooling like dbt, Dagster, and Great Expectations have done an amazing job arming data practitioners with the tools that they need to start adopting the best practices of software engineering like modularity, testing, and release management. This shift in mindset has resulted in
…Tag: Org Structure
Not enough effort has been made to understand the people using data products, what they want to get done, and the broader context in which they operate. I believe there
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I have often found that it is difficult to explain to business stakeholders what exactly a data analyst on my analytics team does. And even beyond that, I have sometimes
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