Everyday Data Science 101 isn't just about learning data science - it's about living it. Through the story of Emily, a small caf owner with no technical background and a lot of questions, this book gently guides readers from curious beginner to confident problem solver. When her afternoon sales start slipping and instinct alone isn't cutting it, Emily turns to data for help - but quickly realizes she doesn't know where to begin. What follows is a warm, practical journey through real-world decision-making, where concepts like data types, cleaning methods, visualizations, basic statistics, and even machine learning are introduced not in theory, but through the everyday dilemmas of running a business.
With each chapter, Emily - and the reader - builds fluency in the core principles of data science, all while solving familiar problems like forecasting demand, designing loyalty programs, and understanding customer patterns. Written in an immersive, narrative expository style, this book doesn't rely on jargon or formulas. It's a mentor-guided, story-driven way to learn data science - from the caf floor to the bigger picture. No prior experience needed, just curiosity and a willingness to think differently.