Artificial Intelligence Improves Adoption of Analytics

Given the value modern analytics can provide, there are going to be many within an industrial organization who will want to create models and consume their output. This includes high-level math experts, such as data scientists, citizen data scientists (such as engineers), as well as field- and back-office workers. Broadening the adoption of analytics across this complex set of users is by no means a simple task. These users often have specific, different, and sometimes competing perspectives on what data is valuable and how it is best used. Adding to this is the vast scale and scope of many industrial value chains, such as oil and gas, where like terms often have different meanings based on process application, multiple languages are used, and many individuals and roles are involved.