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The 4 Data Prep Styles: Picking the Right One

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Most analytics or data science exercises require up to 80% of time be dedicated to profiling, cleaning and transforming data - according to Paxata.

While this can be a taxing process, it ensures raw data can be reliably converted into business-driving decisions and actionable insights. There are a handful of ways to do this, and not every approach is created equal. So how do you know which data prep method will work best for your particular business need?

This e-book reviews the common paradigms and comparison factors that should be considered when evaluating the 4 primary data preparation styles. Read on and uncover the differences between each and see which is ultimately the best fit for your business.

Vendor:
Paxata
Posted:
09 Apr 2019
Published:
31 Dec 2018
Format:
PDF
Type:
eBook
Language:
English

This resource is no longer available.