As heat treating equipment and processes are upgraded and redesigned, there is a significant push towards the inclusion of new sensor technologies, “smart” machines, and the Internet of Things for industrial heat treating operations. There is a clear benefit to being able to track the “health” of equipment in operation, as well as knowing and logging the processing parameters and quality control results in real-time. However, faced with ever increasing datasets containing complementary or contradicting information that are generated by multiple operators, different manufacturer’s equipment, and a variety of brands of PLCs and microprocessors, the heat treat industry is now challenged to create the infrastructure, procedures, and databases to make sense (and use) of these data. This paper explores the methods already in place in similar industries, the ways that data analytics are currently being applied to heat treat operations, and it provides recommendations for future Big Data efforts in our heat treat industry.