Principles of data wrangling: practical techniques for data preparation

Principles of data wrangling: practical techniques for data preparation

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LF/349401/R
Англійська
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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 availableChoose which data to use and at what level of detailMeaningfully combine multiple sources of dataDecide how to distill the results to a size and shape that can drive downstream analysis
LF/349401/R

Характеристики

ФІО Автора
Carreras
Connor
Heer
Hellerstein
Jeffrey Michael
Joseph M.
Kandel
Rattenbury
Sean
Tye
Мова
Англійська
ISBN
9781491938928
Дата виходу
2017

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Principles of data wrangling: practical techniques for data preparation

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 ...

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