What does it really take to bring data science into the enterprise? Or... what does it take to bring it into your part of the enterprise? In this episode, the gang sits down with Dr. Katie Sasso from the Columbus Collaboratory...because that's similar to what she does! From the criticality of defining the business problem clearly, to ensuring the experts with the deep knowledge of the data itself are included in the process, to the realities of information security and devops support needs, it was a pretty wide-ranging discussion. And there were convolutional neural networks (briefly). For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

WHERE were you the first time you listened to this podcast? Did you feel like you were JOINing a SELECT GROUP BY doing so? Can you COUNT the times you've thought to yourself, "Wow. These guys are sometimes really unFILTERed?" On this episode, Pawel Kapuscinski from Analytics Pros (and the Burnley Football Club) sits down with the group to shout at them in all caps. Or, at least, to talk about SQL: where it fits in the analyst's toolbox, how it is a powerful and necessary complement to Python and R, and who's to blame for the existence of so many different flavors of the language. Give it a listen. That's an ORDER (BY?)! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Happy New Year! Sure. The ball has dropped in Times Square, and a new year means an opportunity to look forward. But, we wanted to take a quick look back first -- on the industry, on the podcast, and on the world in general. From GDPR to Bayesian statistics to machine learning and AI to... podcast (and #mattgershoffed) stickers, 2018 was, clearly, the Year of the Analyst. So keep analyzing! 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 had stakeholders complain that they're not getting the glorious insights they expect from your analytics program? Have you ever had to deliver the news that the specific data they're looking for isn't actually available with the current platforms you have implemented? Have you ever wondered if things might just be a whole lot easier if you threw your current platform out the window and started over with a new one? If you answered "yes" to any of these questions, then this might be just the episode for you. Adam "Omniman" Greco -- a co-worker at Analytics Demystified of the Kiss sister who is *not* a co-host of this podcast -- joined the gang to chat about the perils of unmaintained analytics tools, the unpleasant taste of stale business requirements, and the human-based factors that can contribute to keeping a tool that should be jettisoned or jettisoning a tool that, objectively, should really be kept! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

What's the hot new technology of 2018? AI? Deep Learning? Pole-dancing robots? Maybe. Or, maybe it's customer data platforms (CDPs) -- a topic we actually covered way back in January 2017 on episode #053 with Todd Belcher, who, at the time, was with CDP provider BlueConic. Since then, Todd left BlueConic to start CDP Resource, which is, well, a resource for companies looking to select, implement, and maintain a CDP. We asked Todd to come back on the show to give us the rundown on how there is now -- finally -- clarity, consolidation, and maturity in the space, as all of the providers have aligned around a common definition of what a CDP is, what it does, and how it should do it. Alas! The space isn't even remotely there yet! We have yet to even reach the peak of inflated expectations! Which was probably why it was such an informative discussion. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Perspective is a good thing. We've all agonized about a misreported metric or an unsatisfying entry page analysis and had to remind ourselves that we're not exactly saving lives with our work. On this episode, though, the gang actually meanders into life-and-death territory by chatting about one of the uses of data outside of the world of digital marketing and websites and eCommerce: natural disaster preparation and response. Sherilyn Burris from Cascia Consulting joins Michael, Moe, and Tim to chat about her experiences in a variety of roles in just that area, how she uses data, how the data landscape has evolved over the past 15 years, and what she has learned about communicating data to politicians, to the media, and to the general public (which has some intriguing parallels to the communication of data in digital analytics!). For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Remember when you used to keep all of your data packed into data boxes and stacked up on a bunch of data shelves in your state-of-the-art data warehouse? Well, it might be time to fire up the data forklift and haul all of those boxes out of the structured order of your data warehouse and dump them into a data lake so that it can float and sink and swim around in semi-structured and unstructured waters. On this episode, Rohan Dhupelia joins the gang to talk about his thoughts and experiences from engineering just that sort of move at Atlassian. So, pop in your earbuds and strap on your data swim trunks and give it a listen! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

To think, it was barely-considered subtle humor that we used two trailing zeros in episode #001. But, despite our best efforts to destroy our reputations or our livers long before we centupled that original episode, we failed on both fronts, and we now need that third significant digit! For this special episode, we invited listener questions, and our listeners responded. Some of them blew right past the time limit on their questions, but that's okay: we blew (slightly) past the one hour mark for the show. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Are you deeply knowledgable in JavaScript, R, the DOM, Python, AWS, jQuery, Google Cloud Platform, and SQL? Good for you! If you're not, should you be? What does "technical" mean, anyway? And, is it even possible for an analyst to dive into all of these different areas? English philosophy expert The Notorious C.M.O. (aka, Simo Ahava) returns to the show to share his thoughts on the subject in this episode. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

As the axiom goes: people don’t leave companies; they leave their managers. And, good analysts are constantly being approached with new opportunities. So, what’s the secret formula for hanging on to analytics talent? Assuming simply chaining them to their desks isn’t an option, then the trick is keeping them happy and motivated. On this episode, the gang discusses their experiences and perspectives on the topic. Tim tried to quit the show just before recording, but he then discovered that Michael had chained him to his desk. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.