Gary Murphy

Summary

Physics geeks will remember all the fun they had with the simple harmonic oscillator, first in classical mechanics and then in quantum and maybe in QFT if they went that far (can't say I did). But the system is so elegant and insightful that it always seemed a shame to mar it with realistic boundary conditions and lossy terms and nonlinear effects. I say all that to claim that the same sort of tension exists in most of the modern data disciplines and I've come to peace with it: beauty and amazing architectural diagrams are great, but at some point you have to roll up your sleeves and get dirty in order to get the main jobs done and please your customers. Despite my many years working with scientific and oilfield data, I still think the best years of collaborative data workflows are ahead of us, and that the goals my teams have accomplished until now are just steps to something even cooler. To that end, I'm newly energized with the tooling we have at our disposal: cloud platforms, sexy UX tools, and compute power I could only have dreamed of back in the nineties. So let's do it, finally! Let's make a data platform that enables global teams to work on the same data at the same time and with the confidence they need to trust that all their data is consistent with their simulated worlds and the real world. I think the goal is more achievable than ever, but only if we are disciplined and knowledgeable. There are still no shortcuts for the hard stuff. Specialties: E&P data quality paradigms (cartographic reference systems, units, axes of measurement), E&P data management software design, project management, Java/C++ implementation, embedded SQL, Oracle applications, 3D graphics, pattern recognition algorithms, parallel programming, performance engineering, physics, geophysics, Google Cloud Platform, Elasticsearch, Elastic Cloud Enterprise, short and sexy Jupiter notebooks that get to the point I'm trying to make.