Today, over 80% of industrial data is left unanalyzed due to data silos, inconsistent naming, and data fragmentation. Traditional, manual data unification projects have struggled to overcome these challenges and deliver a scalable, unified data model. This whitepaper, “Unified Data Model: Applying Generative AI for Data Unification,” offers a perspective on the role of agentic AI and Small Language Models (SLMs) in reducing manual processes to create a unified data model. This approach can automate data ingestion and normalization, resolve duplicate entities, and integrate knowledge graphs for AI-powered use cases.
Additionally, this whitepaper outlines a clear pathway to achieving a robust data unification process that concurrently yields a unified namespace. Using a midstream oil and gas scenario, see how this AI-driven approach significantly reduces costs and project timelines. While only one industry example is provided, the underlying approach and processes apply to adjacent industrial verticals with similar challenges.
Discover how this cutting-edge technology has the potential to transform industrial data strategies and unlock $1 trillion in global economic value. Download this whitepaper today and gain insights on the future of industrial data management using a unified data model.