big data, business intelligence, and predictive analytics
With all of the hype surrounding big data, business intelligence, and predictive analytics (with the statistics stepchild lurking in the background), quality managers and engineers who wish to get involved in the area may be quickly dismayed by the terminology in use by the various participants. Singular concepts may have multiple names depending on the discipline or problem origin (business analytics, machine learning, neural networks, nonlinear regression, artificial intelligence, and so forth). Hence, there is a pressing need to develop a coherent and comprehensive standardized vocabulary. Subcommittee One of ISO TC69 is currently developing such a terminology standard to reside in the ISO 3534 series. In addition to the technical statistical-type terms, it could also include a discussion of some of the software facilities in use in dealing with massive data sets (HADOOP, Tableau, etc.). A benefit of this future standard is to shorten the learning curve for a big data hopeful. This paper describes the initial steps in addressing the terminology challenges with big data and offers some descriptions of forthcoming products to assist practitioners eager to plunge into this area.