The machines are coming! The machines are coming! Artifiicial Intelligence is here. But what is it, and how long will we have to wait for the technology to completely take over all analysis work? Dennis Mortensen -- founder of x.ai -- joins us on this episode for a deep dive into the topic. You will be surprised by how pragmatic and real AI seems as Dennis describes how he approaches it. And...then his last call will completely blow up the nice, cozy layer of downy comfort that you've settled into during the discussion. So it goes. Artificial intelligences and things referenced in this episode include: x.ai, Alexa, Siri, Cortana, Planet Money Episode #626, Wait But Why on The Fermi Paradox, and Rick and Morty.

Somebody wants to overthink their analytics tools? Tell 'em their dreamin'! We wanted to talk about open source and event analytics and Snowplow sits right at that intersection. Our guest Simon Rumble is the co-founder of Snowflake Analytics and one of the longest users of Snowplow. We wrap up the show with all the places you can find Simon and Tim in the next few months. Fun fact: You will also learn in this episode that conversion funnels go down the opposite direction in Australia. 

Once upon a time, in an industry near and dear, lived an analyst. And that analyst needed to present the results of her analysis to a big, scary, business user. This is not a tale for the faint of heart, dear listener. We're talking the Brothers Grimm before Disney got their sugar-tipped screenwriting pens on the stories! Actually, this isn't a fairy tale at all. It's a practical reality of the analyst's role: effectively communicating the results of our work out to the business. Join Michael and Tim and special guest, Storytelling Maven Brent Dykes, as they look for a happy ending to The Tale of the Analyst with Data to Be Conveyed. Tangential tales referenced in this episode include: Web Analytics Action Hero, Brent Dykes Articles on Forbes.com, The Wizard of Oz, Made to Stick, Data Storytelling: The Essential Data Science Skill Everyone Needs, The Story of Maths, and mockaroo.com.

What IS customer intelligence? What is a customer? Is the customer best understood by breaking the word down into its component parts: "cuss" and "tumor?" Would that be an intelligent thing to do? Will these and related questions some day be answered by self-aware machines? Will any of *these* questions be answered on this episode? Give it a listen and find out! The mish-mash of companies, products, and miscellany mentioned on this show include: Adobe, Oracle/ATG, SAS Customer Intelligence, Salesforce.com, Scott Brinker (Chief Martec), Domo, Data Studio 360, Tableau, iJento, Netezza, SPSS, Unfrozen Caveman Lawyer, Eight Is Enough, Legend of the Plaid Dragon (and the Slack version), Office Vibe, p-value article on fivethirtyeight.com (and the p-hacking app), and the "AI, Deep Learning, and Machine Learning" video.

In this episode, we dive deep on a 1988 classic: Tom Hanks, under the direction of Penny Marshall, was a 12-year-old in a 30-year-old's body... Actually, that's a different "Big" from what we actually cover in this episode. In this instant classic, the star is BigQuery, the director is Google, and Michael Healy, a data scientist from Search Discovery, delivers an Oscar-worthy performance as Zoltar. In under 48 minutes, Michael (Helbling) and Tim drastically increased their understanding of what Google BigQuery is and where it fits in the analytics landscape. If you'd like to do the same, give it a listen! Technologies, books, and sites referenced in this episode were many, including: Google BigQuery and the BigQuery API Libraries, Google Cloud Services, Google Dremel, Apache Drill, Amazon Redshift (AWS), Rambo III (another 1988 movie!), Hadoop, Cloudera, the Observepoint Tag Debugger, Our Mathematical Universe by Max Tegmark, A Brief History of Time by Stephen Hawking, and a video of math savant Scott Flansburg.

As Dr. Phil says, "Never put more into a relationship than you can afford to lose." Not sure what that has to do with Excel but it sounds vaguely wise, which is the whole point. Tim and Michael try to be your relationship coach for Microsoft Excel. Despised by data scientists, but used by everyone else, where are the boundaries and who has what it takes to enforce them. Join us in an exploration of our digital analytics love/hate affair with that most ubiquitous of analytics tools. (Cell) references made in this episode include: Chandoo.org, Juice Analytics, ggplot2, Bullet Charts in Excel, Geeks and Greeks by Steve Altes, Google Firebase.

To outsource or not to outsource -- that is the question: Whether 'tis more efficient to tap The skills and talents of those who bill by the hour, Or to bring resources inside as full-time staff, And, by doing so, manage them. To contract, to outsource -- No more -- and by outsource to say we get Our insights and our implementation work Managed by others -- 'tis a scenario Devoutly to be wished. To contract, to outsource -- To outsource, perchance to analyze. Aye, there's the rub. Besides ignoring iambic pentameter in the process of butchering a Shakespearean reference, this episode, perchance, also makes reference to the following: House of Lies Analytics Made Skeezy Data Smart by John Forman Sim Daltonism

If you're like most analysts, you've probably changed jobs since the last episode of this podcast hit your earbuds two weeks ago. Or, if you haven't actually changed jobs, then you've at least been hounded by recruiters who wish you would. No matter how you look at it, digital analysts have lots of opportunities to bounce between companies at a frequent pace, and many analysts do just that. On this episode, we talk with Dylan Lewis, who has been doing digital analytics at Intuit since before there were federal taxes (give or take a few years). Give it a listen. You just might decide you need a personal board of directors! If nothing else, this episode might inspire you to check out http://careers.intuit.com, which would be ironic given the topic, but definitely understandable!

Back by popular demand: attribution! This time, we brought in an adult on the subject: Jim Novo of The Drilling Down Project. A lot of questions get tackled in this episode: Should "gut feel" ever trump "the data?" Which is a better analogy for attribution: PV=nRT or the distillation of bourbon? Will this podcast *ever* have flawless audio quality? These questions and more definitively answered. All in under 52 minutes.

Are you a data scientist? Have you pondered whether you're really a growth hacker? Well...get over yourself! Picking up on a debate that started onstage at eMetrics, Michael, Jim, and Tim discuss whether a fundamental shift in the role (and requisite skills) of the web analyst are changing. You know, getting more "science-y" (if "science" is "more technical and more maths"). all in 2,852 seconds (each second of which can be pulled into R and used to build a predictive model showing the expected ROI of listening to future episodes; at least, we assume that's what a data scientist could do).