Advancing Digital Twins Beyond Time Series Data: A Framework for Defining and Categorizing Operational Data

Advancing Digital Twins Beyond Time Series Data: A Framework for Defining and Categorizing Operational Data

This IDC Perspective provides insight into what defines operational data and the priority data enterprises are seeking to integrate as part of broader digital twin strategies. Digital twins for industrial operations have made a resurgence in interest for many companies as data-driven operations and analytics initiatives mature. In present market discussions, there is significant ambiguity around the concept of "operational data" and what it is made up of — an ambiguity that creates misalignment between technology users and providers. "Often, operational data is used synonymously with time series data when in reality it is much more," says Jonathan Lang, research director for IDC's Worldwide IT/OT Convergence Strategies. "If we think untangling time series data has been challenging, wait until we get into the structured and unstructured operational data that comes out of function or role-based applications." To understand the work to be done to advance industry capabilities toward data-driven operations, IDC provides in this document a common definition of operational data and utilizes experience with digitally advanced industrial enterprises to help prioritize the data that is in greatest need of standardized integration approaches.

Please Note: Extended description available upon request.