Data Science + Learning Algorithms + High Performance Compute = Competitive Advantage
Data science, high performance computing (HPC) and machine learning algorithms allow organizations to make better decisions and create game-changing strategies. The integration of high quality smart data, computing resources and data scientists using learning algorithms is the secret sauce to achieving the fundamental goal of creating durable competitive advantage.
HPC has evolved in the past decade to provide "supercomputing" capabilities at significantly lower costs and enables data scientists to address challenges that have been unmanageable in the past. HPC expands modeling and simulation capabilities, including using advanced data science algorithm design, machine learning and techniques like random forests, monte carlo simulations, bayesian probability, regression, naive bayes, K-nearest neighbors, neural networks, decision trees and others.
Additionally, HPC allows an organization to conduct controlled experiments in a timely manner as well as conduct research for things that are too costly and time consuming to do experimentally. With HPC you can mathematically model and run numerical simulations to attempt to gain understanding via direct observation.
Public and private organizations in many domains are starting to use HPC, data science and machine learning algorithms to boost strategic thinking, improve operations and innovate to create better services and products.