Watch: What You Need to Know About Big Data Security Analytics

The number of attacks on organization’s’ IT infrastructure is growing exponentially. There were over 700 data breaches in 2015, and at an average cost of $3.79 million, according to research from the Ponemon Institute. That’s a lot of damages.  In particular, it’s becoming increasingly difficult to identify unknown threats. This problem requires the ability to store more data and better tools to analyze the data.

In their research report on the “Evolution of Data Driven Security,” IT analyst firm Enterprise Management Associates (EMA) revealed that big data security analytics is a rapidly growing area of interest for enterprises looking for solutions that bridge the data and security gap. According to EMA’s research, organizations are investing heavily to determine how to get the richest context about their IT environments and utilized the large swaths of data generated by their networks to identify advanced persistent threats, insider attacks, and anything else that threatens their data and, ultimately, their bottom lines.

This on-demand webinar – featuring David Monahan, research director for security and risk management at EMA, Sameer Nori, senior product marketing manager at MapR Technologies, and Nick Amato, director technical marketing at MapR Technologies – covers the convergence of security analytics and big data solutions.

In this hour-long video, Monahan, Nori, and Amato discuss market trends driving businesses towards security analytics, how security analytics differ from Security Information and Event Managment (SIEM), and how technologies such as machine learning enable advanced security analytics.

Jeff Edwards
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Jeff Edwards

Jeff Edwards is an enterprise technology writer and analyst covering Identity Management, SIEM, Endpoint Protection, and Cybersecurity writ large.He holds a Bachelor of Arts Degree in Journalism from the University of Massachusetts Amherst, and previously worked as a reporter covering Boston City Hall.
Jeff Edwards
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