Chad Smykay View Bio
With all the activity going on in your network devices, it can be extremely hard to filter out the bad from the good. How can you quickly and effectively distinguish a network intrusion attempt from an expected and authorized event? A great approach for getting in front of those attacks involves the use of big data technologies for predictive analytics. By analyzing all your network event data with Apache Hadoop and Apache Spark, you can build models that identify “normal” behavior as well as anomalous behavior. The anomalies signal potential security threats, and using Hadoop/Spark gives you the high performance and scalable platform to more accurately alert you to take action.
Chad is a passionate technologist working to enable data analytics for a better business experience with our customers. With over 15 years of operational experience in the Linux and storage systems market he brings real world background in creating new product models as well as the supporting systems for those models. Prior to joining MapR he was one of the first 50 employees at successful startup venture at Rackspace for over 10 years, managing over 3 petabytes of active data storage as well as over 30 petabytes of monthly backup data. Mostly recently he worked within EMC to generate new business utilizing data scientist workflow and data visualization workshops.