DataMesh’s FactVerse Data Fusion Services (DFS) unifies data from multiple sources—such as IoT sensors, enterprise systems, and operational logs—into a single digital environment within FactVerse. By eliminating data silos and providing analytics and ML platform integration, DFS accelerates decision-making, supports continuous optimization, and empowers businesses to harness the full potential of their digital twin strategies.
Data Fusion Services’ Digital Twin Mapping ensures that all virtual entities are continuously updated with real-time data, providing precise and dynamic representations of your facilities for accurate monitoring and informed decision-making.
With robust data cleansing capabilities, Data Fusion Services removes inaccuracies and inconsistencies from raw data, ensuring high-quality, reliable data that supports effective analysis and simulation.
DFS effortlessly connects to a wide range of data sources using standard protocols, unifying data from MES, PLCs, and more. This seamless integration ensures data consistency and eliminates silos, enabling comprehensive operational visibility.
DFS provides a centralized data mart optimized for ML, AI, and BI tools, enabling sophisticated data analysis and intuitive visualization. This empowers businesses to derive actionable insights, optimize processes, and achieve strategic objectives with ease.
Implementing DFS begins by defining clear objectives, such as streamlining real-time data usage or accelerating machine learning initiatives. Next, assess and prepare your existing data sources, whether MES, PLC, or enterprise databases, and identify the protocols (MQTT, OPC UA, etc.) that DFS will use to ingest data. Work with DataMesh or a certified partner to set up and configure the DFS modules—Data Ingestion, Mapping, Cleansing, Computation, Data Mart, and Visualization—to align with your operational needs. Conduct a pilot deployment to validate functionality and performance, then roll out DFS organization-wide with thorough user training and ongoing optimization based on feedback and usage metrics.
DFS follows a license and services model, offering flexibility and scalability for diverse organizational requirements.
The platform’s Data Ingestion module uses standard protocols (MQTT, OPC UA, HTTP, etc.) to pull data from various systems, such as MES or ERP solutions. You can also connect REST APIs or flat-file inputs for additional flexibility. Once ingested, DFS automatically cleanses and maps the data to digital twin entities, creating a unified dataset accessible for analysis, simulation, or AI/ML processing. Collaborating with DataMesh or an integration partner ensures that any unique data formats or custom APIs are properly accommodated, minimizing disruption to existing workflows.
Data Fusion Services recommends using Microsoft Azure as the platform hosting services.
Address：1400 112th Ave SE, Suite 100, Bellevue, WA 98005
Seattle – Tokyo – Beijing – Shanghai – Taipei – Singapore