How to select your integration architecture

Time to read: 4 minutes

Posted by John Harrington

In my last post, “Seven steps to making your industrial data fit for purpose”, I briefly covered seven steps that are critical for manufacturers looking to scale their IIoT projects and wrangle data governance. I’d like to use this post to dive deeper on step 4, selecting your integration architecture, which requires diligence during IIoT planning.

Integration architectures fall in two camps: direct application programming interface (API) connections (application-to-application) or integration hubs (DataOps solutions).

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Direct API connections work well if you only have two applications that need to be integrated. The data does not need to be curated or prepared for the receiving application, and the source systems are very static. This is typically successful in environments where the manufacturing company has a single SCADA or MES solution that houses all the information, and there is no need for additional applications to get access to the data.
 
Direct API connections do not work well when industrial data is needed in multiple applications like SCADA, MES, ERP, IIoT Platform, Analytics, QMS, AMS, cyber threat monitoring systems, various custom databases, dashboards or spreadsheet applications. Direct API connections also do not work well when there are many data transformations that must occur to prepare the data for the consuming system.
 
These transformations can easily be performed in Python, C#, or any other programming language but they are then “invisible” and hard to maintain. Finally, direct API connections do not work well when data structures are frequently changing. This happens when the factory equipment or the programs running on this equipment are frequently changed. For example, a manufacturer may have short-run batches that require loading new programs on the PLCs; the products produced may evolve and require changes to the automation; the automation may be changed to improve efficiency; or the equipment may be replaced due to age and performance.
 
Using the API approach buries the integrations in code. Stakeholders may not even be aware of integrated systems until long after the equipment has been replaced or changes have been made, resulting in undetected bad or missing data for weeks or even months.
 
An alternative to direct API connections is a DataOps integration hub. DataOps is a new approach to data integration and security that aims to improve data quality and reduce time spent preparing data for use throughout the enterprise. An integration hub acts as an abstraction layer that still uses APIs to connect to other applications but provides a management, documentation and governance tool to connect data sources to all the required applications.
 
An integration hub is purpose-built to move high volumes of data at high speeds with transformations being performed in real time while the data is in motion. Since a DataOps integration hub is an application itself, it provides a platform to identify impact when devices or applications are changed, perform data transformations and provide visibility to these transformations.
 
Next Steps
If your next integration project would benefit from an integration hub approach, I invite you to take a closer look at HighByte Intelligence Hub.
 
HighByte Intelligence Hub is the first DataOps solution purpose-built for industrial environments. HighByte Intelligence Hub enables Operations Technology (OT) to securely connect, model, and flow valuable industrial data throughout the enterprise, providing the critical data infrastructure for Industry 4.0.
 
If you’d like to see the software for yourself, please schedule a demo or join our free trial program.