Building a Layers of Analytics Strategy for Operational Data

Part 1: The Foundations for Enabling Transformative Business Value

On-Demand Webinar

In order to leverage the quality of operational data, the scope of the analytics must be understood in the context of the assets involved. Sensor measuring specific traits, the health and status of particular equipment such as a pump, or a functional group of machinery monitoring an overall result, all depend on various measurements and data layered to provide a high-level concept that can be interpreted throughout the entire organization.

The optimal approach to utilizing this data is with SME (subject-matter-expert) knowledge being deployed in fit-for-purpose methods regarding business production or asset maintenance, whether that be reactive, preventive, condition-based or predictive. All of this is possible if a business deploys the right layered analytics strategy.
Join us for part one of a three-part webinar series where we first explore a layered approach to analytics for use cases in data quality, condition-based and predictive maintenance, process diagnostics, and much more. We will introduce the data engineering aspects in the workflow and prepare you for what to expect regarding operationalizing the analytics.

In this webinar, you will learn:

  • The importance of building a “layers of analytics” strategy and the key enablers involved for information management
  • How operating companies are realizing transformative business value from leveraging analytics in a hybrid data lake approach.
  • The best practices associated with evolving layers of analytics underpinned with no code digital twins

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