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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 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
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