Synopsis
Machine learning and computerized data analysis is incredibly powerful, but humans still excel at "getting a sense of things"―the ability to recognize ill-defined or novel patterns or anomalies. With the rise of real-time streaming data, it’s important to give people access to data as it arrives, in ways that enable users or analysts to recognize that "something is going on." This book provides both conceptual guidance and programming tools to do just that.
Streaming data is a fast-moving part of the data field: tools for analysis on streaming and real-time data are at the cutting edge, and visualization of these types of data hasn’t caught up. This guide helps close the gap by showing application designers, data scientists, data miners, data journalists, and system administrators several ways to create visualizations that bring context and a sense of time to streaming text data.
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About the Author
Anthony Aragues is currently the Vice President of Product Management at Anomali. Anthony brings a wide range of technical and business experience to guide security products. He started his career in technology and security in the military in 1997. He has been focused on Threat Intelligence since 2008 with the start of McAfee's Global Threat Intelligence program where he was an inventor of multiple threat intelligence patents. He was most recently leading engineering and product management at Norse across all products. Anthony has a Computer Information Systems degree from Strayer University. Anthony is a life long technology enthusiast who learns, programs, and tinkers every chance he gets.
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