How to Be a Good Analyst

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Julian Zelizer: If you are too specialized in an area, then you're used to seeing a lot of problems from the same point of view. He says that's when you get a really bad outcome compared to someone who has more varied experience. "I believe you cannot be a good analyst unless you have mastered QA before like you move on," he adds.

There are only so many hours in a day and only so many days in a year. Logically, then, the best way to grow a career as a data worker is to spend as many hours as possible doing focused data work, right? Well… probably not. In this episode, we dove into generalization versus specialization — what does that even mean, and how should we think about balancing between the two, and how can interests and activities outside of the data work itself actually make us better analysts? Bonus activity: listen for the hosts' overt trolling of Tim to see if they can get him to come off mute in his role as associate producer for the episode. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.