Principles of Data Wrangling: Practical Techniques for Data Preparation

Principles of Data Wrangling: Practical Techniques for Data Preparation
1491938927
Principles of Data Wrangling: Practical Techniques for Data Preparation
by: Tye Rattenbury – Joseph M. Hellerstein – Jeffrey Heer – Sean Kandel – Connor Carreras
ISBN-10: 1491938927
ISBN-13: 9781491938928
Edition 版次: 1
Publication Date 出版日期: 2017-07-15
Print Length 页数: 94
9


Book Description
By finelybook

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 practical guide 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?”
Wrangling data consumes roughly 50-80% of an analyst’s time before any kind of analysis is possible. Written by key executives at Trifacta,this book walks you through the wrangling process by exploring several factors—time,granularity,scope,and structure—that you need to consider as you begin to work with data. You’ll learn a shared language and a comprehensive understanding of data wrangling,with an emphasis on recent agile analytic processes used by many of today’s data-driven organizations.
Appreciate the importance—and the satisfaction—of wrangling data the right way.
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
Contents
Chapter 1. Introduction
Chapter 2. A Data Workflow Framework
Chapter 3. The Dynamics of Data Wrangling
Chapter 4. Profiling
Chapter 5. Transformation: Structuring
Chapter 6. Transformation: Enriching
Chapter 7. Using Transformation to Clean Data
Chapter 8. Roles and Responsibilities
Chapter 9. Data Wrangling Tools

相关文件下载地址

打赏
未经允许不得转载:finelybook » Principles of Data Wrangling: Practical Techniques for Data Preparation

评论 抢沙发

觉得文章有用就打赏一下

您的打赏,我们将继续给力更多优质内容

支付宝扫一扫

微信扫一扫