Complete eight data science projects that lock in important real world skills-along with a practical process you can use to learn any new technique quickly and efficiently. The Well-Grounded Data Analyst guides you through eight common scenarios you'll encounter as a data scientist or analyst. As you explore each project, you'll also master a proven process for quickly learning new skills developed by author and Half Stack Data Science podcast host David Asboth. In The Well-Grounded Data Analyst you'll learn: - High-value skills to tackle specific analytical problems
- Deconstructing problems for faster, practical solutions
- Data modeling, PDF data extraction, and categorical data manipulation
- Handling vague metrics, deciphering inherited projects, and defining customer records In The Well-Grounded Data Analyst you'll learn how to shift the way you think about data from the structured clean problems you get in a classroom, book, or bootcamp to the messy open-ended challenges of the workplace. As you work through eight problems you'll see over and over on the job, you'll discover a solutions-driven methodology that's focused on getting results. You'll learn how to determine a minimum viable answer for your stakeholders, identify and obtain the data you need to deliver, and reliably present and iterate on your findings. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the book The Well-Grounded Data Analyst presents eight industry scenarios that you're sure to encounter in your data science career. The book can be read cover-to-cover, or opened up to whichever chapter is most relevant to your current challenges. You'll explore data modeling by identifying customer records from retail transactions, navigate badly defined metrics, and learn how to extract data from PDFs as you analyze how COVID-19 changed the film industry. Get your hands dirty with categorical data that defies conventional statistical analysis, and unearth hidden patterns in seemingly simple time series data. Plus, you'll learn what to do when you're handed someone else's work to expand on, and how to wow your stakeholders with your presentations. By the time you're done reading and working, you'll have the kind of on-the-job skills it normally takes years to learn--and an amazing portfolio of projects to show off at an interview. About the reader For early-career data scientists. You know the technical basics--this book