Big Data: Technologies for Business
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Imported Edition - Ships in 18-21 Days
Free Shipping in India on orders above Rs. 500
***An eTextbook version is available at VitalSource.com for $52.85 USD. ISBN: 978-1-958303-46-7.***
The availability of big data is increasing as is the need for people to prepare and analyze it. Big Data Technologies for Business seeks to fill this need by presenting the material in a manner accessible to a broad audience including non-technical managers, business students and other professionals. Big data technologies are no longer the exclusive province of dedicated computer programmers. This book assumes little or no prior programming experience. Topics are introduced conceptually, intuitively, with pseudocode, and with fully worked examples including code. In this manner, students learn to use various essential technologies including, among others, Spark, Hadoop, and Amazon Web Services (AWS).
Edition 2.0 has been comprehensively revised to bring it up-to-date given the extensive changes that have occurred and to maintain accuracy into the future.
New Features:
Cover the latest technologies
Coverage of those technologies currently in widespread use (especially Spark and Hadoop 3.4) has been expanded. Coverage of deprecated technologies (e.g., Apache Sqoop) has been removed.
Provide accurate web-based tutorials
Edition 1.0 had tutorials included in the text itself. This limited our ability to respond to configuration drift. For Edition 2.0, tutorials are now available on our website. The authors are committed to responding to any changes and challenges as they arise in the future. Should you identify an inaccuracy or code segment that no longer works, get in touch, and we will have it updated.
Showcase data preparation
A new chapter explores the nature of data and its processing for use in big data applications.
Emphasize use of Python
Python is used as the crosscutting programming language for all assignments. Use of Java and Scala have been de-emphasized. The website provides some Java and Scala code, particularly if it was used in the previous edition.
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