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Python: Data Analytics and Visualization

You're reading from   Python: Data Analytics and Visualization Perform data processing and analysis with the help of python libraries, gain practical insights into predictive modeling and generate effective results in a variety of visually appealing charts using the plotting packages in Python

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Product type Course
Published in Mar 2017
Publisher Packt
ISBN-13 9781788290098
Length 866 pages
Edition 1st Edition
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Authors (4):
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Martin Czygan Martin Czygan
Author Profile Icon Martin Czygan
Martin Czygan
Ashish Kumar Ashish Kumar
Author Profile Icon Ashish Kumar
Ashish Kumar
Kirthi Raman Kirthi Raman
Author Profile Icon Kirthi Raman
Kirthi Raman
Phuong Vo.T.H Phuong Vo.T.H
Author Profile Icon Phuong Vo.T.H
Phuong Vo.T.H
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Toc

Chapter 1. A Conceptual Framework for Data Visualization

The existence of the Internet and social media in modern times has led to an abundance of data, and data sizes are growing beyond imagination. How and when did this begin?

A decade ago, a new way of doing business evolved: of corporations collecting, combining, and crunching large amount of data from sources throughout the enterprise. Their goal was to use a high volume of data to improve the decision-making process. Around that same time, corporations like Amazon, Yahoo, and Google, which handled large amounts of data, made significant headway. Those milestones led to the creation of several technologies supporting big data. We will not get into details about big data, but will try exploring why many organizations have changed their ways to use similar ideas for better decision-making.

How exactly are these large amount of data used for making better decisions? We will get to that eventually, but first let us try to understand...

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