The modern data stack (MDS) is the defining paradigm informing how new organizations use technology to leverage data. Lots of digital ink has been spilled, and takes are growing ever spicier on all things MDS. Here’s a more benign one:
The Modern Data Stack currently focuses too much on tooling and would be more effective if it refocused on the humans using the tools. In particular, the MDS ecosystem doesn’t currently address implementation,
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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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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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As an analytics leader, my job is to ensure that my organization makes the best data-driven decisions possible. One effective mechanism that I employ — and other analytics leaders can too — is the business review program. This program is a rigorous and systematic review of the most important Key Performance Indicators (KPIs) across the company, with involvement by senior leadership in an ongoing and iterative fashion, punctuated by a regularly occurring cross-functional meeting. …
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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Key Performance Indicators (KPIs) are management tools for monitoring and improving business processes. KPIs are helpful in understanding if you’re hitting your business objectives, improving over time, and helping to
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As the new year rolls around, many Data leaders are thinking about (or have already created) 2019 road maps for their team and function. Since Data often works cross functionally
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I often get asked by junior data professionals how they can improve as data scientists. Today I will outline a generic framework for thinking about learning and provide a few
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A hypothetical tech company just completed an A/B test of two experiences, A (the test) and B (the control). The test was set up properly and executed successfully. The following
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