Ever wondered if Hollywood’s magic is just smoke and mirrors, or if there’s actually some cold, hard data behind those blockbuster hits? I sat down with Stephen Follows, the film data analyst who’s basically Indiana Jones, but instead of chasing ancient artifacts, he’s digging up the buried truths of the movie industry. We’re talking about […] The post Dear Anal...

There are times when a problem nags at you like a pebble in your shoe. Even when you’re not working on the problem itself, you’re thinking about the problem which make it even worse. Rarely do I come across a Google Sheets/Excel task I cannot solve with formulas, but this one evaded my extensive knowledge […] The post Dear Analyst #133: Find or check if a cell contains text from...

When you think of your data warehouse, the “semantic layer” may not be the first thing that pops in your mind. Prior to reading Frances O’Rafferty‘s blog post on this topic, I didn’t even know this was a concept that mattered in the data stack. To be honest, the concept is still a bit confusing […] The post Dear Analyst #132: How the semantic layer translates yo...

If you could only learn one programming language for the rest of your career, what would be it be? You could Google the most popular programming languages and just pick the one of the top 3 and off you go (FYI they are Python, C++, and C). Or, you could pick measly #10 and build […] The post Dear Analyst #131: Key insights and best practices from writing SQL for 15+ years with Ergest Xheblat...

This is a replay of an episode from the Make Sense podcast with Lindsay Tabas. In the 1990s, large enterprises typically bought software in a tops-down approach. IT teams would get get Oracle software or Microsoft Office and get their entire organization to use the software. Since these tools are the default IT “blessed” tools, people start […] The post Dear Analyst #130: What ha...

When you’re organization is small, a centralized data team can take care of all the internal data tooling, reporting, and requests for all departments. As the team grows from 100 to thousands of people, a centralized data team simply cannot handle the number of requests and doesn’t have the domain knowledge of all the departments. […] The post Dear Analyst #129: How to scale self...

This is a replay of an episode from the Citizen Development Live podcast with Neil Miller. Citizen development is a relatively new term I learned about a year ago or so. To me, it’s using no-code tools at scale within a large enterprise. It’s a term that covers the population of people who are not […] The post Dear Analyst #128: What is citizen development and how to build soluti...

I wasn’t sure if this topic should be it’s own episode but it’s been on my mind ever since I came back from Atlassian Team ’24 (Atlassian’s annual conference). At the conference, I had the opportunity to meet with a few people who are just as interested in spreadsheets as I am. We talked specifically […] The post Dear Analyst #127: Spreadsheets vs. Jira: Which o...

With an undergraduate degree in zoology and a master’s in public health, you wouldn’t expect Amanda Makulec to lead a successful career in data analytics and data visualization. As we’ve seen with multiple guests on the podcast, the path to a career in data analytics is windy and unexpected. It was the intersection of public […] The post Dear Analyst #126: How to data story...

Sometimes pop culture and data analysis meet and the result is something interesting, thought-provoking, and of course controversial. How can one use data to prove definitely which Taylor Swift songs are the most underrated? Isn’t this a question for your heart to answer? Andrew Firriolo sought to answer this question over the last few months […] The post Dear Analyst #125: How to iden...