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Big Data Science & Analytics: A Hands-On Approach, by Arshdeep Bahga Vijay Madisetti
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About the Author
Arshdeep Bahga is a Research Scientist with Georgia Institute of Technology. His research interests include cloud computing and big data analytics. Arshdeep has authored several scientific publications in peer-reviewed journals in the areas of cloud computing and big data. Vijay Madisetti is a Professor of Electrical and Computer Engineering at Georgia Institute of Technology. Vijay is a Fellow of the IEEE, and received the 2006 Terman Medal from the American Society of Engineering Education and HP Corporation.
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Product details
Paperback: 542 pages
Publisher: VPT; 1 edition (April 15, 2016)
Language: English
ISBN-10: 0996025537
ISBN-13: 978-0996025539
Product Dimensions:
7 x 1.2 x 10 inches
Shipping Weight: 2 pounds (View shipping rates and policies)
Average Customer Review:
4.0 out of 5 stars
7 customer reviews
Amazon Best Sellers Rank:
#604,433 in Books (See Top 100 in Books)
There are very few comprehensive and current books about the broadrange of Big Data Analytics which are suitable for use as universitytextbooks for the the subject. Bahga and Madisetti's book is anexception, introducing the characteristics of Big Data projects,surveying modern analytic concepts and methods, and including avariety of illustrative and relevant case studies. While not goinginto great depth on the use of specific software tools, the bookdoes provide enough introductory guidance for further explorationof such topics as Hadoop, NoSQL, and many of their related toolsfor data management and analysis. Additional tool-specific referencescan then be used to augment their coverage.The authors' explanations are clear with numerous helpful diagramsand code examples using Python and other programs. They includebrief instructions for using online Big Data services such as thoseprovided by Hortonworks, Cloudera, Amazon Web Services, and Azure.As a textbook, this reference is quite suitable for introductoryData Analytics courses, as it presents the "big picture" of thisemerging and rapidly evolving area of technology. The instructors'website for the book does not yet include sample presentations norstudent exercises, but these are easily created from the basematerial.The authors clearly prefer Python and related tools over R foranalysis, and there is little mention of the latter in the book.However, that too is easily augmented by instructors who wish toinclude R in their courses for students with less programmingexperience.
I love this book. It is so much of a straightforward "how-to". One of the better intro books out there.
Really nice, good price
Not user friendly.I appreciate the content in the book, but it does not really say how to connect and such basic stuff with which readers will get stuck with for years.
The book was used but it looks like new.A very good coverage of the subject. I would highly recommend this book for anyone interested in knowing more about Big Data.This is a good book in terms of "foundation".
I like the way authors have presented the analytics patterns. There are individual chapters focused on batch, real-time and interactive analytics, that provide a good overview of the big data frameworks. The case studies are very helpful. Overall the book is easy to read.
Comprehensive and organized. Lots of examples and case studies in this relatively new area of big data analytics.
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