BigDataFr recommends: Data Analytics is the key skill for the modern engineer

[…] Many process manufacturing owner-operators in this next phase of a digital shift have engaged in technology pilots to explore options for reducing costs, meeting regulatory compliance, and/or increasing overall equipment effectiveness (OEE).

Despite this transformation, the adoption of advanced analytics tools still presents certain challenges. The extensive and complicated tooling landscape can be daunting, and many end users lack fundamental understanding of process data analytics. Combined with a lack of awareness of the practical benefits that analytics offer, this leaves many engineers stuck in day-to-day tasks, using spreadsheets and basic trend analysis tools for the bulk of their daily analysis.

In this article we discuss the need for improved analytics awareness for the modern process engineer. We also explore key considerations in creating such awareness and the capabilities that state-of-the-art self-service analytics tools offer for process performance optimization.

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By Thomas Dhollander, co-founder and VP of Products at TrendMiner, expert in algorithm design and time series analytics for process data.
Source: dataconomy.com