English | 2020 | PDF | 14 MB | 268 Pages
Ben Jones, B081H61XNH, 1119278163, 1119278171, 9781119278160, 9781119278177, 9781119278207, 978-1119278160, 978-1119278177, 978-1119278207
Avoid data blunders and create truly useful visualizations
Avoiding
Data Pitfalls is a reputation-saving handbook for those who work with
data, designed to help you avoid the all-too-common blunders that occur
in data analysis, visualization, and presentation. Plenty of data
tools exist, along with plenty of books that tell you how to use
them—but unless you truly understand how to work with data, each of
these tools can ultimately mislead and cause costly mistakes. This book
walks you step by step through the full data visualization process,
from calculation and analysis through accurate, useful presentation.
Common blunders are explored in depth to show you how they arise, how
they have become so common, and how you can avoid them from the outset.
Then and only then can you take advantage of the wealth of tools that
are out there—in the hands of someone who knows what they're doing, the
right tools can cut down on the time, labor, and myriad decisions that
go into each and every data presentation.
Workers
in almost every industry are now commonly expected to effectively
analyze and present data, even with little or no formal training. There
are many pitfalls—some might say chasms—in the process, and no one
wants to be the source of a data error that costs money or even lives.
This book provides a full walk-through of the process to help you
ensure a truly useful result.
- Delve into the "data-reality gap" that grows with our dependence on data
- Learn how the right tools can streamline the visualization process
- Avoid common mistakes in data analysis, visualization, and presentation
- Create and present clear, accurate, effective data visualizations
To
err is human, but in today's data-driven world, the stakes can be high
and the mistakes costly. Don't rely on "catching" mistakes, avoid them
from the outset with the expert instruction in Avoiding Data Pitfalls.
