Exploring the guest's transition from software development to data analysis, and their evolution towards becoming a data generalist specializing in data science education. The chapter emphasizes the importance of practical skills like handling office dynamics and formulating strong research queries in the context of the data science field.
“All data scientists and analysts should spend more time in the business, outside the data sets, just to see how the actual business works. Because then you have the context, and then you understand the columns you’re seeing in the data."
David Asboth, author of “Solve Any Data Analysis Problem” and co-host of the “Half Stack Data Science” podcast, shares practical tips for solving real-world data analysis challenges. He highlights the gap between academic training and industry demands, emphasizing the importance of understanding the business problem and maintaining a results-driven approach.
David offers practical insights on data dictionary, data modeling, data cleaning, data lake, and prediction analysis. We also explore AI’s impact on data analysis and the importance of critical thinking when leveraging AI solutions. Tune in to level up your skills and become an indispensable, results-driven data analyst.
Listen out for:
- Career Journey - [00:01:38]
- Half Stack Data Science Podcast - [00:06:33]
- Real-World Data Analysis Gaps - [00:10:46]
- Understanding the Business/Problem - [00:15:36]
- Result-Driven Data Analysis - [00:18:28]
- Feedback Iteration - [00:21:44]
- Data Dictionary - [00:23:48]
- Data Modeling - [00:27:18]
- Data Cleaning - [00:30:43]
- Data Lake - [00:35:05]
- Common Data Analysis Tasks - [00:36:50]
- Prediction Analysis - [00:40:23]
- The Impact of AI on Data Analysis - [00:43:15]
- Importance of Critical Thinking - [00:47:05]
- Common Tasks Solved by AI - [00:50:07]
- 3 Tech Lead Wisdom - [00:53:10]
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David Asboth’s Bio
David is a “data generalist”; currently a freelance data consultant and educator with an MSc. in Data Science and a background in software and web development. With over 6 years experience teaching, he has taught everyone from junior analysts up to C-level executives in industries like banking and management consulting about how to successfully apply data science, machine learning, and AI to their day-to-day roles. He co-hosts the Half Stack Data Science podcast about data science in the real world and is the author of Solve Any Data Analysis Problem, a book about the data skills that aspiring analysts actually need in their jobs, which will be published by Manning in 2024.
Follow David:
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