Smart grid data analytics technology not the problem for utilities


Utilities know that "big data" is quickly turning into "huge data." But did you know that utilities globally are investing billions to deploy and implement smart grid technologies to modernize their operational and information systems so they can monitor, analyze, and synchronize their networks to improve reliability, availability, and efficiency?

This is according to Pike Research, who says that smart grid data analytics are a crucial part of fully realizing these investments.

Simply analyzing well-structured meter and monitoring data may no longer be enough to understand how a utility can improve its business. Data analytics engines must be able to process non-structured data from non-traditional sources by examining raw data from smart grid sensors and devices along with other forms of operational data and external third-party data.

"Data analytics are the next level of intelligent network control and planning," said Pike Senior Research Analyst Bob Lockhart. "The application of smart grid data analytics is challenging, because it involves collating and analyzing data from many internal sources, plus integrating non-structured data from external sources such as demographics, social media, emails, and images, to effectively support decision-making."

Smart grid analytics is complex. There is no straightforward answer to the technology-buying decisions related to the acquisition and employment of smart grid analytics that utility CTOs and CIOs must make.  

Delivery of data will be just as complex, coming through dashboards, complex visualizations, general reporting, alarms, alerts, modeling and statistical analysis, simulation, and time series analysis.

Data analytics is not a technology problem for utilities. The real problem lies in deeply understanding the business to effect meaningful change, while finding the right technology to meet those needs, according to Lockhart.

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