This practical guide shows how data wrangling, the process of converting raw data into something truly useful, can be achieved. Authors Tye Rattenbury, Joe Hellerstein, Jeffrey Heer, Sean Kandel and Connor Carreras provide business analysts with an overview of various data wrangling techniques and tools, and put the practice of data wrangling into context by asking, "What are you trying to do and why?"

Wrangling data consumes roughly 50-80% of an analyst's time before any kind of analysis is possible. Written by executives at Trifacta (who have a platform for exploring and preparing data for analysis), the book explores several factors--time, granularity, scope, and structure.

Author: Tye Rattenbury, Joe Hellerstein, Jeffrey Heer, Sean Kandel and Connor Carreras
Publisher: O'Reilly
Date: July 2017
Pages: 94
ISBN: 978-1491938928
Print: 1491938927
Kindle: B073HMH8XG
Audience: Data managers
Level: Introductory
Category: Data Science

• Understand what kind of 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

For recommendations of Big Data books see Reading Your Way Into Big Data in our Programmer's Bookshelf section.

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