(287e) Collaboration Is Critical for Effective Deployment of Big Data Analytics

Manufacturers across the world have begun their digital transformations with an eye towards utilizing big data analytics. With this effort, process sensors are providing a wealth of data, numerous machine learning algorithms are being developed, and data scientists are being hired at an astounding rate. While these advancements are important, the reality is that a wealth of key information, or context, is typically not captured in any database. That wealth of information is the internal expertise that subject matter experts, like engineers and scientists, rely on to drive effective decision making. Considering this, an effective analytics strategy must utilize technology and workflows that combine both human experience and computer technology.

In collaboration, subject matter experts are relied upon throughout the project to provide relevant context, document assumptions, and explain applicable constraints. Data scientists complement this information with their knowledge of machine learning algorithms and other relevant analytics options. Together, the team finds the hidden patterns in the data that translate to business value for the company.

This session will provide a framework for leveraging analytics applications to promote effective collaboration between subject matter experts and data scientists to accelerate the time to insight and operationalize models and algorithms. The presentation will cover the importance of subject matter expert involvement in data preparation for successful deployment of models and algorithms through a series of examples of effective analytics deployment. Examples include operations selected from a variety of industries, including pharmaceuticals and chemicals.