Big Data in Energy & Utilities
A OT and IT data analytics platform is required as a core capability to deal with volume, variety, velocity and complexity of data we are facing. Smart Grid initiatives will produce big data. Historian systems offer some beginnings but are often ‘guarded’ and only contain a subset of data. The concept of an Engineering Data Warehouse is getting some traction - tis requires the platform and capabilities which are still developing.
Tradition information usage has been focussed on why things happened with some data mining to uncover detail of past events. The focus is slowly shifting to use information to look forward but progress is slow. Some organizations are looking at pattern recognition to use information to look forward and better react to increasing data volumes - including predictive analysis. In memory DBMS systems are enabling some of these activities. Information sharing is a key principle of a pattern based strategy - breaking down data silos.
One example presented using to approach to predict equipment failure using both structured and unstructured data - including visual information. This capability plays a central role in reliability engineering & predictive asset management.
Most vendors can handle the high volumes of data, that’s not the challenge. The challenge is getting and using the right blend (starting with historian and EDW) of data. Gartner’s Information Capabilities Framework was presented as a potential enabler.
Operational visualization is key to making big data useful and accessible. ABB are doing quite a bit in this area through acquiring some key IT companies.
IT and OT need to work together to understand the business needs, develop appropriate strategies and build a data analysis capability to support big data. I think we need to start by picking some low hanging fruit to build relationships through results.