Reducing OT Data Management and Systems Integration Costs Using Cloud Solutions

Data lakes store unstructured data from multiple sources in its native form (i.e., historian, asset monitoring, process data); a data warehouse stores well-defined, structured information (i.e., ERP, CRM, MRP data). Both are cloud solutions. Below are truncated definitions from Gartner:
 

• Data lake – collects unrefined data (that is, data in its native form, with limited transformation and quality assurance) and events captured from a diverse array of source systems.
• Data warehouse – houses well-known and structured data; supports predefined and repeatable analytics needs that can be scaled across many users.
• Operational technology (OT) – hardware and software that detects or causes a change by directly monitoring and/or controlling industrial equipment, assets, processes, and events.

Essentially, OT data originates from a plethora of systems already familiar to customers:
 

• Programmable logic controllers (PLCs)
• Distributed control systems (DCS)
• Safety instrumented systems (SIS)
• Computerized maintenance management systems (CMMS)
• Operational/plant historians (e.g., OSI PI)
• Manufacturing execution systems (MES)
• Asset management systems (AMS)
• Continuous emissions monitoring systems (CEMS)
• Wired/wireless sensor data with software/online condition monitoring (IIOT)

The depth and breadth of OT data found in most plants pose challenges to organizations seeking IT/OT integration. OT data is diverse and lives in many different databases. Dedicated point-to-point interfaces live between the user application data and create costly and complex architectures with dozes to hundreds of interfaces across the enterprise.

 

Connecting to the data that resides in the OT system poses the most difficult challenges. Most customers will want to get data to the cloud at an enterprise scale but will not know how to connect to the data in these systems without disrupting them. And cloud connectivity for point solutions doesn’t scale effectively, gets expensive quickly, and is often challenging to manage from a central location. Some of the questions we encounter include:
 

• How do I tunnel DCS data across firewalls (L2-L5 security) and land it in an enterprise cloud?
• How do I ensure I don’t break or disrupt any of my OT systems?
• How do I access stranded data and combine multiple OT data streams from a single site?
• How do I transfer the data through a single TCP connection across multiple firewalls?
• When network connections are lost, how do I Store and Forward (SaF) data from my OT systems?

To truly digitally transform an organization’s analytics and systems consolidation initiative, customers need to consider a platform approach that is efficient and robust enough to satisfy IT’s requirements and effectively manage the use cases required by OT and plant operations.

 

Emerson’s data lake solution closes the IT/OT data management gap by offering an OT data-centric, single platform compatible with enterprise cloud providers. The solution includes the interoperability software IT and OT leaders will need to achieve their integration requirements. Finally, sites can implement Emerson’s data lake solution without disrupting their OT systems and mission-critical production processes.