bookbestseller Posted February 27 Report Share Posted February 27 The Well-Grounded Data Analystby David AsbothEnglish | 2025 | ISBN: 1633437531 | 474 pages | True PDF EPUB | 94.68 MBComplete 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.Data analysts need to be problem solvers-andThe Well-Grounded Data Analystwill teach you how to solve the most common problems you'll face in industry. You'll explore eight scenarios that your class or bootcamp won't have covered, so you can accomplish what your boss is asking for.InThe Well-Grounded Data Analystyou'll learn:High-value skills to tackle specific analytical problemsDeconstructing problems for faster, practical solutionsData modeling, PDF data extraction, and categorical data manipulationHandling vague metrics, deciphering inherited projects, and defining customer recordsTheWell-Grounded Data Analystis for junior and early-career data analysts looking to supplement their foundational data skills with real-world problem solving. 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 hostDavid Asboth. 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. The book can be read cover-to-cover or opened to the chapter most relevant to your current challenges.Foreword byReuven M. Lerner.About the technologyReal world data analysis is messy. Success requires tackling challenges like unreliable data sources, ambiguous requests, and incompatible formats-often with limited guidance. This book goes beyond the clean, structured examples you see in classrooms and bootcamps, offering a step-by-step framework you can use to confidently solve any data analysis problem like a pro.About the bookThe Well-Grounded Data Analystintroduces you to eight scenarios that every data analyst is bound to face. You'll practice authorDavid Asboth'sresults-oriented approach as you model data by identifying customer records, navigate poorly-defined metrics, extract data from PDFs, and much more! It also teaches you how to take over incomplete projects and create rapid prototypes with real data. Along the way, you'll build an impressive portfolio of projects you can showcase at your next interview.What's insideDeconstructing problemsHandling vague metricsData modelingCategorical data manipulationAbout the readerFor early-career data scientists.About the authorDavid Asbothis a data generalist educator, and software architect. He co-hosts the Half Stack Data Science podcast.Table of Contents1 Bridging the gap between data science training and the real world2 Encoding geographies3 Data modeling4 Metrics5 Unusual data sources6 Categorical data7 Categorical data: Advanced methods8 Time series data: Data preparation9 Time series data: Analysis10 Rapid prototyping: Data analysis11 Rapid prototyping: Creating the proof of concept12 Iterating on someone else's work: Data preparation13 Iterating on someone else's work: Customer segmentationA Python installation instructionsRapidGatorhttps://rg.to/file/b06aa38541c09e50e62f6fc02a7f99f6/yzhhl.7z.htmlTakeFilehttps://takefile.link/l52rdcitj2rj/yzhhl.7z.htmlFileaxahttps://fileaxa.com/44zbnz56lvpw/yzhhl.7zFikperhttps://fikper.com/g8qU3yJRRr/yzhhl.7z.html Link to comment Share on other sites More sharing options...
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