Transcending database tuning problems: How machine learning helps DBAs play more ping pong
Machine learning enables businesses to gain competitive advantage through predictive analytics. But if we look deeper into the data stack, we find the need for the same predictive capabilities for MySQL tuning. With over 1013 possible tuning permutations, some requiring reboots or a rebuild, DBAs spend too much time on MySQL tuning for a point-in-time situation that changes constantly. This session will show how unsupervised machine learning based on resource, workload and information modeling can predictively and continuously tune databases. DBAs transcend the tuning game, saving precious time to work on important things, like improving your mad ping pong skills!
Chief Strategy Officer, Deep Information Sciences
Chad Jones is the chief strategy officer at Deep Information Sciences, developing and driving product and go-to-market strategy as well as leading awareness efforts. In his previous role at LogMeIn, he drove product and go-to-market strategy for the company's Xively IoT platform and evangelized the company's vision for the Internet of Things. Prior to LogMeIn, Chad served as VP, strategy and PM for DynamicOps (cloud automation software) acquired by VMware in 2012. Before DynamicOps, he was VP, Product Management with Neocleus (client hypervisor) acquired by Intel. Chad was also a creator of SoftGrid (app virtualization) from Softricity, acquired by Microsoft, which grew to revenues topping $4.2B. He also maintains his own investment fund named Plesso Ventures, Inc., providing strategic guidance as well as investing in great companies across multiple industries including technology, beer, wine, alternative energy, next generation concealed fastening systems, sporting goods and wireless electricity. Chad has more than 18 years' experience driving strategic initiatives for startups and F50 companies alike, and has traveled the planet discussing a vision for a better world through technology.