Embracing Data Analytics: From Excel to Python

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The chapter explores the transformative experience of transitioning from Excel to Python for data analysis, emphasizing the importance of personal initiative and following passions. It discusses the challenges faced by analysts in adapting to new analytical techniques, the necessity of continuous growth, and the risk of getting distracted by trendy tools. The speaker shares insights on overcoming imposter syndrome and lack of confidence when transitioning to the technical side of analytics from a non-maths or stats background.

Is it just us, or does it seem like we're going to need to start plotting the pace of change in the world of analytics on a logarithmic scale? The evolution of the space is exciting, but it can also be a bit dizzying. And intimidating! There's so much to learn, and there are only so many hours in a day! Why did we choose that [insert totally unrelated field of study] degree program?! These questions and more—including a quick explanation of bootstrapping for Tim’s benefit, which is NOT bootstrapping or bootstrap—are the subject of the latest episode of the show, with Kirsten Lum, the CTO of storytellers.ai, joining us to discuss strategies and tactics for the technically-non-technical analyst to thrive in an increasingly technical analytics world. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.