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Do you long for the days when your mother could ask you, "Now, what do you actually do for your job?" and "all" you had to do was explain websites and digital analytics? The "analyst" is now a role that can be defined an infinite number of ways in its breadth and depth. Is the analyst who is starting to do data transformations to create clean views still an analyst? Or is she a data engineer? A data scientist? On this episode, we explore the idea of an "analytics engineer" with Claire Carroll from Fishtown Analytics who, while she did not coin the term, can certainly be credited with its growth as a concept. And there is a brief but intense spat about the role of "analytics translator," which Claire sat out, but observed with bemusement. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Did curiosity kill the cat? Perhaps. A claim could be made that a LACK of curiosity can (and should!) kill an analyst's career! On this episode, Dr. Debbie Berebichez, who, as Tim noted, sorta' pegs out on the extreme end of the curiosity spectrum, joined the show to explore the subject: the societal norms that (still!) often discourage young women from exploring and developing their curiosity; exploratory data analysis as one way to spark curiosity about a data set; the (often) misguided expectations of "the business" when it comes to analytics and data science (and the imperative to continue to promote data literacy to combat them), and more! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
How does a Bayesian tell what time it is? She starts with an estimated time as her prior and then makes a video for TikTok. If you've ever made a joke like that and then realized your audience might need a little statistical education in order to appreciate how hilarious it is (or, perhaps, what the probability is that it's hilarious), then this episode is for you. The Chatistician (and the creator of the #statstiktok hashtag), Chelsea Parlett-Pelleriti, joined the show to talk about tactics for making statistics accessible, both to ourselves and to others! Humor and thoughtfulness were both normally distributed throughout the discussion. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Once every four years in the United States, there is this thing called a "presidential election." It's a pretty boring affair, in that there is so much harmony amongst the electorate, and the two main candidates are pretty indistinguishable when it comes to their world views, policy ideas, and temperaments. But, despite the blandness of the contest, digging in to how the professionals go about forecasting the outcome is an intriguing topic. It turns out that forecasting, be it of the political or the marketing variety, is chock full of considerations like data quality, the quantification of uncertainty, and even () the opportunity to run simulations! On this episode, we sat down with G. Elliott Morris, creator of The Crosstab newsletter and a member of the political forecasting team for The Economist, to chat about the ins and outs of predicting the future with a limited set of historical data and a boatload of uncertainty. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Do you know someone who always seems to have read the latest books and can cite concepts and ideas and authors and titles in any situation? Do you hate that person? Honestly, so do we. But that didn't stop us from recording an episode that, potentially, will grate on your nerves in such a way that you have to draw on your inner grit (Grit: The Power of Passion and Perseverance by Angela Duckworth) to get through it. But, with luck, there will be some good ideas that make it into your long-term memory (Brain Rules: 12 Principles for Surviving and Thriving at Work, Home, and School by John Medina), and it will be information delivered in a gender-neutral manner, unlike so much of the world (Invisible Women: Exposing Data Bias in a World Designed for Men by Caroline Criado-Perez). Give it a shot, though. It may help you become a better leader in your organization (Dare to Lead by Brené Brown).
Unfortunately, we lost some of this episode (even our recording platform was tired of hearing about books?). We know what we talked about then, even if we have no audio record, so we've included those books in the show notes as well. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Analytics is hard (so they say... but we're not going to open THAT can of worms). Do you know what's harder? Managing analysts! I mean, they're always asking, "Why?" Sometimes, they even ask it five times! They can wind up, you know, analyzing whatever you're asking them to do! On this episode, special guest Moe Kiss (you may know her as a co-host of this podcast) joined Michael and Tim to dig into the ins and outs of the analyst/manager relationship. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
A wise man once said, "All forecasts basically assume that tomorrow is going to be very similar to today, just with an adjustment or two." That wise man was Gary Angel from Digital Mortar, and he said that on this very episode as we explored the ramifications for the analyst when the historical data is not at all a proxy for the near-term and medium-term future. What is the analyst to do when her training data has become as worthless as a good, firm handshake? If your prediction—based on listening to past episodes—is that Gary and our intrepid co-hosts might actually have some sharp ideas on the subject, well, give this show a listen and see how well you did! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Remember back when the global economy was booming and analysts were both in the sexiest job of the century and on the favorable side of the supply-demand curve for talent? Those were the days! On this episode, we sat down with Ollie Darmon from Canva to get his perspective, as an in-house recruiter, on what candidates can and should do to not only get in the door, but to actually close the deal and get hired. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
No one has ever been disappointed by a sequel, right? Especially when the original was well-received both by the critics and at the box office. Well, Episode #134: "These Are a Few of Our Favorite (Analytics) Tips" scored an 83% Tomatometer with an audience score of 91% on Rotten Tomatoes. As it happened, those are the same scores that The Sound of Music achieved, and they're pretty impressive. Unlike The Sound of Music, we decided we'd give our fans what they clearly wanted and release another episode of our (just as favorite) analytics tips! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
A hallmark of the analytics community is the generosity with which ideas and wisdom are shared. One of the largest analytics conferences each year is Adobe Summit. One of the most followed Tims on the planet wrote a book called Tribe of Mentors: Short Life Advice from the Best in the World. Jen Yacenda and Eric Matisoff mixed all three of these truths together in preparation for an hour-long presentation chock full of excellent career advice. And then Adobe Summit went virtual, and their session got drastically shortened. On this episode, Jen joined the gang to talk through (some of) the 11 questions that they posed to 38 analysts, the responses they got, and how she and the hosts answered the questions themselves. 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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