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Stand: 2020-01-07
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Raghu Kodali, Peter Zadrozny (Beteiligte)

Big Data Analytics Using Splunk


Deriving Operational Intelligence from Social Media, Machine Data, Existing Data Warehouses, and Other Real-Time Streaming Sources
1st ed. 2013. xv, 376 S. 304 SW-Abb. 254 mm
Verlag/Jahr: SPRINGER, BERLIN; APRESS 2013
ISBN: 1-430-25761-X (143025761X)
Neue ISBN: 978-1-430-25761-5 (9781430257615)

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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
Part I: Splunk´s Basic Operation: Getting to Know Splunk Part I: Splunk´s Basic Operation: Getting Data into Splunk Part I: Splunk´s Basic Operation: Processing and Analysing the Data Part I: Splunk´s Basic Operation: Visualizing the Results Part I: Splunk´s Basic Operation: Defining Alerts. Part I: Splunk´s Basic Operation: Web Site Monitoring Part I: Splunk´s Basic Operation: Using Log Files to Create Advanced Analytics Part II: Airline On-Time Performance Project: On-Time Project Description Part II: Airline On-Time Performance Project: Getting Flight Data Into Splunk Part II: Airline On-Time Performance Project: Analyzing Airlines, Airports, Flights, and Delays Part II: Airline On-Time Performance Project: Analyzing a Specific Flight over Time Part III: Social Media: Analyzing Twitter Data Part III: Social Media: Analyzing Foursquare Check-Ins Part III: Social Media: Sentiment Analysis Part IV: Architecture and Deployment: Distributed Topologies Part IV: Architecture and Deployment: High Availability Appendix A: The Performance of Splunk Appendix B: Related Applications
Peter Zadrozny is an independent consultant specialized in big data, software performance, and architecture. He is also a lecturer on big data topics at San Jose State University. He has held various executive and technical roles in many countries around the world for startups as well as Fortune 500 companies. He started the operations of WebLogic in Europe and Sun Microsystems in Mexico. He is an accomplished author with various successful books, a magazine, and was an original contributor to The Grinder, a popular open source project.