The Large Hadron Collider will commence Run 4 in 2026, collecting over 100 times more data than was used to discover the Higgs. This unprecedented dataset, 3 ab-1, will enable precision measurements and searches for new physics and rare processes in ways not done before. To analyze this large dataset the field of particle physics will have to employ new approaches, many of which will be generalizable outside the field. These include using big-data techniques from the business world as well as pushing the frontiers of statistical modeling and adapting machine learning techniques to physics problems. Several large collaborations have been built to organize this effort, including IRIS-HEP, by the NSF. This talk will explore the motivations and the some of these techniques as well as how the field is trying to systematically attack the problem.