Authors:
- Big Data Analytics Using Splunk is a hands-on book showing how to process and derive business value from big data in real time.
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Table of contents (18 chapters)
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Front Matter
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Back Matter
About this book
Big Data Analytics Using Splunk is a hands-on book showing how to process and derive business value from big data in real time. Examples in the book draw from social media sources such as Twitter (tweets) and Foursquare (check-ins). You also learn to draw from machine data, enabling you to analyze, say, web server log files and patterns of user access in real time, as the access is occurring. Gone are the days when you need be caught out by shifting public opinion or sudden changes in customer behavior. Splunk’s easy to use engine helps you recognize and react in real time, as events are occurring.
Splunk is a powerful, yet simple analytical tool fast gaining traction in the fields of big data and operational intelligence. Using Splunk, you can monitor data in real time, or mine your data after the fact. Splunk’s stunning visualizations aid in locating the needle of value in a haystack of a data. Geolocation support spreads your data across a map, allowing you to drill down to geographic areas of interest. Alerts can run in the background and trigger to warn you of shifts or events as they are taking place.
With Splunk you can immediately recognize and react to changing trends and shifting public opinion as expressed through social media, and to new patterns of eCommerce and customer behavior. The ability to immediately recognize and react to changing trends provides a tremendous advantage in today’s fast-paced world of Internet business. Big Data Analytics Using Splunk opens the door to an exciting world of real-time operational intelligence.
- Built around hands-on projects
- Shows how to mine social media
- Opens the door to real-time operational intelligence
About the authors
Bibliographic Information
Book Title: Big Data Analytics Using Splunk
Book Subtitle: Deriving Operational Intelligence from Social Media, Machine Data, Existing Data Warehouses, and Other Real-Time Streaming Sources
Authors: Peter Zadrozny, Raghu Kodali
DOI: https://doi.org/10.1007/978-1-4302-5762-2
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Peter Zadrozny and Raghu Kodali 2013
Softcover ISBN: 978-1-4302-5761-5Published: 22 May 2013
eBook ISBN: 978-1-4302-5762-2Published: 23 August 2013
Edition Number: 1
Number of Pages: XV, 376
Number of Illustrations: 304 b/w illustrations
Topics: Big Data, Information Systems and Communication Service