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The Analytics Power HourEpisodes
Tim Wilson
The Analytics Power Hour
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It happens occasionally. Someone in the business decides they need to just take the analysis into their own hands. That leaves the analyst conflicted — love the interest and enthusiasm, but cringe at the risk of misuse or misinterpretation. Occ
Data communities have played a major role in the careers of many analysts, but times they are a-changin'. We're not sure if we're different, if the communities' purposes and missions have shifted, or both. One thing we are confident in, though,
Long-time listeners to this show know that its origin and inspiration was the lobby bar of analytics conferences—the place where analysts casually gather to unwind after a day of slides interspersed with between-session conversations initiated
As a general rule, analysts are drawn to precision: let's understand the business problem and then go figure out how the data can be acquired and crunched to provide something specific and useful. Fair enough. Where, then, do pencil and paper a
They say an analysis is only as good as the question that was asked, so for our 2024 International Women's Day Episode, Julie, Moe, and Val were joined by Taylor Buonocore Guthrie to discuss how to ask better questions. Every analyst is natural
Is it just us, or does it seem like we're going to need to start plotting the pace of change in the world of analytics on a logarithmic scale? The evolution of the space is exciting, but it can also be a bit dizzying. And intimidating! There's
The post #238: The Many Problems in Dealing with Data Problems appeared first on The Analytics Power Hour: Data and Analytics Podcast.
The post #237: Crossing the Chasm from the Data to Meaningful Outcomes with Kathleen Maley appeared first on The Analytics Power Hour: Data and Analytics Podcast.
The post #236: The AI Ecosystem with Matthew Lynley appeared first on The Analytics Power Hour: Data and Analytics Podcast.
The post #235: 2023 Year in Review with Josh Crowhurst appeared first on The Analytics Power Hour: Data and Analytics Podcast.
The post #234: Establishing Expectations for Analysts appeared first on The Analytics Power Hour: Data and Analytics Podcast.
The post #233: Analytics Mentors (Having One, Being One) appeared first on The Analytics Power Hour: Data and Analytics Podcast.
The post #232: The Reality of Uncertainty Meets the Imperative of Actionability with Michael Kaminsky appeared first on The Analytics Power Hour: Data and Analytics Podcast.
The post #231: Estimating the Effort for Analytics Projects appeared first on The Analytics Power Hour: Data and Analytics Podcast.
The post #230: First, We Must Discover. Then, We Can Explore. With Viyaleta Apgar appeared first on The Analytics Power Hour: Data and Analytics Podcast.
The post #229: Data and the ABCs (SERIES A, B, and C, That Is!) with Samantha Wong appeared first on The Analytics Power Hour: Data and Analytics Podcast.
The post #228: What AI Can’t Do with Dr. Brandeis Marshall appeared first on The Analytics Power Hour: Data and Analytics Podcast.
The post #227: Demystifying Complex Data Science Concepts for Non-Technical Audiences with Dr. Nicholas Cifuentes-Goodbody appeared first on The Analytics Power Hour: Data and Analytics Podcast.
The post #226: Training Analysts to be Curious and Use Business Context with MaryBeth Maskovas appeared first on The Analytics Power Hour: Data and Analytics Podcast.
The post #225: From Stakeholder Buy-In to Stakeholder Knowledge of What That Means appeared first on The Analytics Power Hour: Data and Analytics Podcast.
The post #224: The Chronic Undervaluing of Analyst Communication Skills appeared first on The Analytics Power Hour: Data and Analytics Podcast.
To trust something, you need to understand it. And, to understand something, someone often has to explain it. When it comes to AI, explainability can be a real challenge (definitionally, a "black box" is unexplainable)! With AI getting new leve
There comes a time in every analyst's career where they consider starting up their own consultancy. Or, if not that, then at least joining an agency or a consultancy. The nature of most businesses is to grow, and with growth comes the potential
What causes us to keep returning to the topic of causal inference on this show? DAG if we know! Whether or not you're familiar with directed acyclic graphs (or… DAGs) in the context of causal inference, this episode is likely for you! DJ Rich,
Data gets accessed and used in an organization through a variety of different tools (be they built, bought, or both). That work can be quick and smooth, or it can be tedious and time-consuming. What can make the difference, in modernspeak, is t
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