cloud historian eot

Data Historians are an integral part of, but not limited to, the manufacturing, oil and gas, and energy industries, capturing and storing millions of data points per second. Traditional Data Historians had narrow access lanes to fetch data for analytics or reconciliation purposes.

Firewalls protect any insecure access requests from networks from enterprise networks or external network devices. For this reason, the Demilitarized Zones (DMZs) act as a gatekeeper to get and respond to authorized data requests from Enterprise network devices.

But, the solution is ineffective for devices outside the Enterprise Network or if any requests come from the Enterprise VPNs that are geographically separated. Cloud Historians play a significant role in expanding the data availability across IIoT networks and extending the availability of traditional data historians to a host of enterprise network devices and applications.

Twin Central as Cloud Historian

The rapid change toward digital transformation in heavy industries is increasing the demand for digital solutions that are tailor-made to meet business requirements. According to industry reports, the global Data Historian market is growing at a 5.8% CAGR (Global Market Study On Data Historian In Energy, Utilities & Data Centers, n.d.). Twin Central is a revolutionary solution that makes digital manufacturing easier and more effective for the next generation of industrial IoT.

Twin Central is a combination of data extraction, aggregation, and analytics platforms built for the effective channeling of industrial data. Twin Talk (for data integration) and Twin Central (for data aggregation) platforms capture data from Traditional Historians or Pi servers and channel it for data aggregation.

Capabilities of Twin Central

As a Cloud Historian, Twin Fusion has the characteristics of a typical Cloud Historian, which is the bare minimum for Data Historians platforms operating in the Cloud. Here are some of the capabilities of Twin Fusion.

Real-time Data Ingestion

Twin Talk handles real-time data ingestion from Industrial IoT systems or Pi servers and routes the data securely to a data aggregation platform. It captures data in two modes,

  1. Real-time data stream 
  2. Historical data stream 

The data stream is pushed into the data aggregation platform, like Twin Central, without any transformation or data cleaning on-the-fly. The data ingestion rate is at par with the sampling speeds of the Industrial IoT systems. For example, a mining unit needs real-time data ingestion from asset tracking devices on mining trucks to forecast the production and allocate resources to achieve daily mining tonnage.


Built as a solid SaaS platform leveraging the capabilities of Big Data and Distributed Computing, Twin Fusion is always open to handling the increasing demands of the Industrial IoT. All the resources used for computing, storage, networking, and data exchange scale up as a unit to serve a rapid surge in data streams. For example, As Big Data is gaining popularity among the industry, the demand for Cloud Data Historian is increasing rapidly. (Global Market Study On Data Historian In Energy, Utilities & Data Centers, n.d.)

Digital Twin

Creates a virtual replica of the physical assets in the industrial setup to make a perfect Digital Twin. Beyond just a software model that organizes the industrial assets into a Digital Twin, it helps in predictive maintenance or manufacturing by running the virtual Twin setup on all possible industrial parameter sets. The Formula 1 cars are fitted with IoT sensors feeding data into its Digital Twin to run simulations and find the best race strategy to send back to the driver. (Haponik, n.d.)

Data Security

Data historians restricted access from external devices considering the inherent data vulnerability in the IoT networking environment. Using Twin Fusion’s Twin Talk solution, it is easier to securely exchange data from any traditional Data historian or Pi servers to any other enterprise network. For instance, SMBs and other medium sized industrial units need a Cloud Data protection portfolio to secure data from cyber threats.

Data Visualization

The ultimate goal of Data Historians is to help industry personnel understand plant operations visually. Data visualization is the cream on the cake to educate industry personnel and help plant managers oversee industry operations beyond boundaries.

Twin Sight package is a perfect visualization application that looks back and reads in data from the Twin Central platform to build impressive visualizations and helps project the facts hidden in industrial data.

Twin Fusion is a unified Industrial Data Fabric that has integration, aggregation, and visualization product suites providing end-to-end solutions for Data historian, Visualisation, and Industrial data distribution.

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