Pipeline integrity is embracing the technologies that have been produced by the Big Data revolution. Database access, machine learning algorithms, and analytics tools are no longer the domain of researchers and IT experts, and can be easily deployed to improve our use of pipeline integrity data.
We will discuss the data governance requirements borrowed from Big Data as applied to CP, a case study involving CP measurements with differing levels of data structure, and rules and lessons learned related to the Big Data approach.
