Big data analytics refers to the strategy of analysing large volumes of data, or big data. Industries hold and share large volumes of data including customer data, which is common to many other service businesses, asset and operational data, which may be shared both within the organisation and to external providers and third-party data, which may include data sought or transferred to a variety of agencies.
Up to recently organisations have not had the computing power to analyse big data, nor the bandwidth to transfer it. Both these issues are close to being addressed and will not long prevent big data analysis.
The key issue that needs to be addressed by organisations and utilities is what data do they have access to and what do they wish to do with it. This is one of the key issues that needs to be answered by organisations and utilities over the next few years. Failure to undertake this will result in big data analytics becoming vendor lead.
On the retail side of the water value chain, “clustering algorithms” are proving useful in finding the root cause of discrepancies in consumption, metering, and billing. Analyses enabled by big data can highlight many of the discrepancies that traditionally exist in billing and metering.
This is currently a technology that is not well advanced within the Australian Industries, but due to the amount of data held by organisations, utilities and their supply chain, has huge potential. It is likely to be central to many of our business by 2030.
David Nixon has worked the utilities industry for over 30 years across a variety of utilities, engineering and business consultancies. David currently acts as director and advisor to a variety of organisations across Australia. firstname.lastname@example.org