With proliferation of Internet and Cloud Technologies, several options are now available to acquire and analyse both real-time sensor data and other types of asset data (e.g. images, manual inspection results etc.), using Industrial IoT (Internet of Things), SCADA, Historian, MES (Manufacturing Execution Systems), Condition Based Asset Management solutions etc. These systems, if deployed correctly could all play their part in an organisation, but also has the potential of creating more data silos if not designed judiciously. 

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We see these diverse data sources as agents for Collaboration and Digital Transformation, which, with the right context, present a holistic view of the state of an asset or process. The actual process of data integration remains transparent to the user. Thus, the business manager can focus on the various KPIs and metrices that impact the plant operations and performance without having to worry about how to capture data from all these sources.

We believe that collecting large volumes of data and running analytics on them is not the only way to gain insights. On the contrary, this approach might lead to several issues. Thus, we use Sparse Data Representation (SDR) techniques to encode the collected data and enhance the Semantics.