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.
…Category: Management
Data teams aim to help the people in their organization make better decisions. Many data teams aren’t doing this as well as they could and are missing out on a
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In part 2 of this series, we learned that every new initiative a team undertakes should be accompanied by an expectation on how the initiative will perform. For example,
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The MBR meeting is the focal point of the MBR program. Here you will publicly interrogate KPIs, align on action items and hold people accountable. There are typically
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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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KPIs are central to the business review program since they provide a way to reason about the success or failure of an initiative. Core to the success of a
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It’s becoming more and more clearly recognized that the promises of the machine-learning revolution, at least for your average non-big-tech company, are not delivering the value that many had hoped
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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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