Principles of Data Wrangling: Practical Techniques for Data Preparation

Principles of Data Wrangling: Practical Techniques for Data Preparation
Principles of Data Wrangling: Practical Techniques for Data Preparation by Tye Rattenbury
English | 2017 | ISBN: 1491938928 | 94 Pages | EPUB, AZW3, PDF (conv) | 10 MB

A key task that any aspiring data-driven organization needs to learn is data wrangling, the process of converting raw data into something truly useful. This book provides business analysts with an overview of various data wrangling techniques and tools, and puts the practice of data wrangling into context by asking, "what are you trying to do and why?" The authors walk you through the wrangling process by exploring several considerations you need to take into account as you begin to work with data, including time, granularity, scope, and structure.
One of the first lessons you’ll learn in this special preview edition of the book is how data wrangling is a different process than data analysis. In fact, roughly 50-80% of an analyst’s time is spent wrangling data to the point where any kind of analysis is possible. Wrangling involves a set of tasks that enable you to:

  • Understand what data is available
  • Choose which data to use and at what level of detail
  • Meaningfully combine multiple sources of data
  • Decide how to distill the results to a size and shape that can drive downstream analysis

This book provides you with a shared language and a comprehensive understanding of data wrangling, with an emphasis on recent and quickly growing agile analytic processes in data-driven organizations. You’ll come to appreciate the importance—and the satisfaction—of wrangling data the right way.