September 2015
Beginner to intermediate
52 pages
1h 51m
English
Content preview from Getting Data Right
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Chapter 4. Understanding Data Science: An Emerging Discipline for Data-Intensive Discovery
Over the past two decades, Data-Intensive Analysis (DIA)—also referred to as Big Data Analytics—has emerged not only as a basis for the Fourth Paradigm of engineering and scientific discovery, but as a basis for discovery in most human endeavors for which data is available. Though the idea originated in the 1960s, widespread deployment has occurred only recently, thanks to the emergence of big data and massive computing power. Data-Intensive Analysis is still in its infancy in its application and our understanding of it, and likewise in its development. Given the potential risks and rewards of DIA, and its breadth of application, it is imperative that we get it right.
The objective of this new Fourth Paradigm is more than simply acquiring data and extracting knowledge. Like its predecessor, the scientific method, the objective of the Fourth Paradigm is to investigate phenomena by acquiring new knowledge, and to integrate it with and use it to correct previous knowledge. It is now time to identify and understand the fundamentals. In my research, I have analyzed more than 30 large-scale use cases to understand current practical aspects, to gain insight into the fundamentals, and to address the fourth “V” of big data—veracity, or the accuracy of the data and the resulting analytics.
Data Science: A New Discovery Paradigm That Will Transform Our World
Big data has opened the ...
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