Many of us data leaders have come of age in a long period of growth, ever-increasing tech valuations, and relative headcount abundance. We are summer’s children, but we’re entering tumultuous times, and it’s relatively clear that winter is coming. Unfortunately, for many companies, that will mean layoffs.
In these early weeks and months of the shift, data teams, along with product and engineering, have been relatively less hard-hit by layoffs than other functions according to
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Your team invested a lot of effort into building self-service data tools, but your stakeholders aren’t using it as much as you hoped, or in the ways that you hoped.
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Getting regular feedback from your organization can help the data team to prioritize the work that will have the biggest impact on your stakeholders. However, it’s hard to turn ad-hoc
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The nuances of data projects add an extra layer of challenge to project planning and agile project management approaches. Even the most efficient data team must manage the inherent moving-target
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Your data team has to produce solid data. The pipelines have to run, the logic in your transformations has to be sound, and the report has to show accurate revenue.
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Providing clarity and structure around expectations empowers your team members to decide what skills and competencies to focus on improving. However, writing the career ladder is only the beginning of
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After last week, I hope you’re on board that a career ladder is important, so let’s jump right into creating one that works for your team. This post will walk
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