
As industrial environments become more connected, organizations are collecting unprecedented volumes of operational data. However, without a consistent way to organize and define that data, it can be difficult to integrate systems, enable analytics, or support advanced use cases like AI.
This guide explains the role data modeling plays in creating a structured and scalable industrial data foundation. Readers will gain a clear understanding of what data modeling is, how it works within industrial architectures, and how it aligns with established standards such as ISA-95. The guide also outlines practical considerations for building a data-modeling strategy that supports interoperability, improves data accessibility, and enables more informed operational decisions.
