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Somewhere between "welcome to the company, now get to work!" and weeks of tedious orientation sessions (that, presumably, include a few hours with the legal department explaining that, should you be on a podcast, you need to include a disclaimer that the views expressed on the podcast are your own and not those of the company for which you now work), is a happy medium when it comes to onboarding an analyst. What is that happy medium, and how does one find it? It turns out the answer is that favorite of analyst phrases: "it depends." Unsatisfying? Perhaps. But, listeners who have been properly onboarded to this podcast know that "unsatisfying" is our bread and butter. So, in this episode, Moe and Michael share their thoughts and their emotional intelligence on the subject of analyst onboarding, while Tim works to make up for recent deficiencies in the show's use of the "explicit" tag. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Have you ever thought it would be a great idea to have a drink or two, grab a microphone, and then air your grievances in a public forum? Well, we did! This episode of the show was recorded in front of a live audience (No laugh tracks! No canned applause!) at the Marketing Analytics Summit (MAS) in Las Vegas. Moe, Michael, and Tim used a "What Grinds Our Gears?" application to discuss a range of challenges and frustrations that analysts face. They (well, Moe and Tim, of course) disagreed on a few of them, but they occasionally even proposed some ways to address the challenges, too. To more effectively simulate the experience, we recommend pairing this episode with a nice Japanese whiskey, which is what the live audience did! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Did you hear the one about how the AI eliminated cancer? It just wiped out the human race! As machine learning and artificial intelligence are woven more and more into the fabric of our daily lives, we are increasingly seeing that decisions based purely on code require a lot of care to ensure that the code truly behaves as we would like it to. As one high profile example after another demonstrates, this is a tricky challenge. On this episode, Finn Lattimore from Gradient Institute joined the gang to discuss the different dimensions of the challenge! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
What's in a job title? That which we call a senior data scientist by any other job title would model as predictively...
This, dear listener, is why the hosts of this podcast crunch data rather than dabble in iambic pentameter. With sincere apologies to William Shakespeare, we sat down with Maryam Jahanshahi to discuss job titles, job descriptions, and the research, experiments, and analysis that she has conducted as a research scientist at TapRecruit, specifically relating to data science and analytics roles. The discussion was intriguing and enlightening!
For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Remember that time you ran a lunch-and-learn at your company to show a handful of co-workers some Excel tips? What would have happened if you actually needed to fully train them on Excel, and there were approximately a gazillion users*? Or, have you ever watched a Google Analytics or Google Tag Manager training video? Or perused their documentation? How does Google actually think about educating a massive and diverse set of users on their platform? And, what can we learn from that when it comes to educating our in-house users on tool, processes, and concepts? In this episode, Justin Cutroni from Google joined the gang to discuss this very topic!
For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
A simple recipe for a delicious analytics platform: combine 3 cups of data schema with a pinch of JavaScript in a large pot of cloud storage. Bake in the deployment oven for a couple of months, and savory insights will emerge. Right? Why does this recipe have both 5-star and 1-star ratings?! On this episode, long-standing digital analytics maven June Dershewitz, Director of Analytics at Twitch, drops by the podcast's analytics kitchen to discuss the relative merits of building versus buying an analytics platform. Or, of course, doing something in between!
The episode was originally 3.5 hours long, but we edited out most of Michael's tangents into gaming geekdown, which brought the run-time down to a more normal length.
For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
We're not sure what's going on with this episode. For some reason, we have a bunch of first-time listeners, and they're all from Apple devices! Maybe it's because the show only comes out every two weeks, and the first-party cookies we've been using to track our listeners are now expiring after seven days! (This is a hilarious episode description if you're well-versed in the ins and outs and ethical and philosophical aspects of WebKit's Intelligent Tracking Prevention (ITP) 2.1. If you're not, then you might want to listen to the gang chat with Kasper Rasmussen from Accutics about the topic, as it's likely already impacting the traffic to your site!)
For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Have you ever attended a conference? Did you know that analysts over-index towards introversion?* Have you ever struggled to figure out how to start a conversation over a cold pastry and a cup of tepid coffee at a conference breakfast? IS there actually a point in developing and executing a strategy when it comes to attending a conference? Is it annoying to listen to people who speak pretty regularly at conferences pontificate about speaking at conferences? Some of these questions are answered on this episode!
For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
*We made this up, but it seems plausible.
Are you a data scientist? I mean, are you really a data scientist? What does that even mean...other than a healthy salary increase? On this episode of the show, Ian Thomas, Chief Data Officer for Publicis Spine sat down with the three co-citizen-data-scientists who regularly host the show to delve into the subject!
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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