『The Analytics Power Hour』のカバーアート

The Analytics Power Hour

The Analytics Power Hour

著者: Michael Helbling Moe Kiss Tim Wilson Val Kroll and Julie Hoyer
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Attend any conference for any topic and you will hear people saying after that the best and most informative discussions happened in the bar after the show. Ready any business magazine and you will find an article saying something along the lines of "Business Analytics is the hottest job category out there, and there is a significant lack of people, process and best practice." In this case the conference was eMetrics, the bar was….multiple, and the attendees were Michael Helbling, Tim Wilson and Jim Cain (Co-Host Emeritus). After a few pints and a few hours of discussion about the cutting edge of digital analytics, they realized they might have something to contribute back to the community. This podcast is one of those contributions. Each episode is a closed topic and an open forum with some combination of Michael, Moe, Tim, Val, and Julie - the goal is for listeners to enjoy listening to them share their thoughts and experiences and, hopefully, take away something to try at work the next day. マネジメント マネジメント・リーダーシップ マーケティング マーケティング・セールス 経済学
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  • #286: Metrics Layers. Data Dictionaries. Maybe It's All Semantic (Layers)? With Cindi Howson
    2025/12/09

    Semantic layers are having something of a moment, but they're not actually new as a concept. Ever since the first database table was designed with cryptic field names that no business user could possibly understand, there's been a need for some form of mapping and translation. Should every company be considering employing a semantic layer? Is the idea of a single, comprehensive semantic layer within an organization a monolithic concept that is doomed to fail? These questions and more get bandied about on this episode, where we were joined by industry legend Cindi Howson, Chief Data & AI Strategy Officer at Thoughtspot.

    For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

    This episode's Measurement Bite from show sponsor Recast is an explanation of multicollinearity from Michael Kaminsky!

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    56 分
  • #285: Our Prior Is That Many Analysts Are Confounded by Bayesian Statistics
    2025/11/25

    Before you listen to this episode, can you quantify how useful you expect it to be? That's a prior! And "priors" is a word that gets used a lot in this discussion with Michael Kaminsky as we try to demystify the world of Bayesian statistics. Luckily, you can just listen to the episode once and then update your expectation—no need to simulate listening to the show a few thousand times or crunch any numbers whatsoever. The most important takeaway is that you'll know you've achieved Bayesian clarity when you come to realize that human beings are naturally Bayesian, and the underlying principles behind Bayesian statistics are inherently intuitive.

    This episode's Measurement Bite from show sponsor Recast is a brief explanation of statistical significance (and why shorthanding it is problematic…and why confidence intervals are generally more practically useful in business than p-values) from Michael Kaminsky!

    For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

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    1 時間 7 分
  • #284: I Used to Think...But Not Any More
    2025/11/11

    As the world turns, a couple of things happen: 1) we grow and learn, and 2) the world changes. On this episode, inspired by a job interview question, the hosts walked through a range of thoughts and beliefs they had at one time that they no longer have today. Analytics intake forms are good…or bad? Analytics centers of excellence are the sign of a mature organization…or they're just one of many potential options? Privacy concerns are something no one really cares about…or they are something everyone cares deeply about? Voices were raised. Light profanity was employed. Laughter ensued.

    This episode's Measurement Bite from show sponsor Recast is a brief explanation of statistical significance (and why shorthanding it is problematic…and why confidence intervals are often more practically useful in business than p-values) from Michael Kaminsky.

    For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

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    1 時間 8 分
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