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Energy customers use process historians, a set of time-series database applications, to collect and store data from industrial systems and sensors. Hosting process historians on the cloud can improve performance monitoring, supervisory control, analytics, and quality assurance. Historian Extension solutions on AWS help customers migrate historians to the cloud for high availability, extend historians by synchronizing process data and asset metadata with industrial data lakes, and modernize data architectures for improved functionality.
TwinTalk, an event-driven, real-time data sharing platform, enables you to read, write, monitor and stream large amount of operational sensor data bi-directionally between operational system (such as OSIsoft PI) and public/private clouds, data lakes, platforms, and AI, ML or analytics applications.
Twin Central – Intuitive industrial digital twin builder that provides semantic asset modelling, mapping and management from operational, engineering and transactional metadata sources.
A simple approach to create and manage an asset-centric, single source of truth and semantic data model across the enterprise. Twin Central can create digital twin data models that map, connect, link, store, and synchronize relationships between assets and their operational, engineering and financial metadata using a unified digital twin relationship graph.
Seeq's extensive support for time series data and its inherent challenges enables process engineers, managers, teams and data scientists to derive more value from data already collected by accelerating analytics, publishing, and decision making.
Advanced time-series data analytics for operational experts in the process manufacturing industries to analyze, monitor and predict process and asset performance to improve operational excellence.