Predictive Analytics and Machine Learning: “Real” Use Cases for IT/Security Professionals

John Platais

John Platais

Speaker Bio

John Platais owns Enterprise Capacity Planning and Performance Management for the world’s largest provider of banking and payment technologies.  His responsibilities include managing a global team of data scientists, analysts, and engineers dedicated to integrating machine learning, “corrective” automation, and “predictive” business intelligence into global data center operations ensuring both stability and security.  John holds a Masters of Science in Organizational Leadership with a focus on developing data strategies for organizational sustainability and advancement.  In his spare time, He enjoys spending time with his wife and kids, taking family vacations, woodworking, and designing new CAD creations for his 3D Printer.

Presentation

We have all heard the phrase, “Hindsight is 20/20.”  Usually this resonates as we stand across from our employer admitting some level of guilt for a recent disaster.  What if we could predict the future with some degree of acceptable accuracy?  What if we knew ahead of time which employee candidate would introduce risk to our organization? What if we were able to pinpoint which of the thousands of current, cyber security threats would have the greatest impact on our unique technology footprint and prioritize those in real time for remediation?  What if we had the ability harvest and incorporate the limitless data available both privately and publicly into our decision making processes without investing millions?

This session will answer those questions and more as we explore the data mining and machine learning options available to all of us using only the technology resources we have at our disposal.   We will be looking at security specific use cases for predictive analytics that will appeal to all security professionals.  We will look at insights and opportunities that can be realized from public data repositories and social media sites where even the most private of us reveal more than we know.

Every participant will leave with the knowledge and direction to begin incorporating machine learning and “AI” into their regular deliverables.  They will learn what tools are available, what value each of those tools can provide, and what data can yield the greatest results in the shortest amount of time.