Complementing Hadoop and Other Batch Processing Big Data Analytics

How Vitria OI Complements Hadoop and Other Offline Big Data Analytics for Energy Firms

Energy and utilities firms continue to amass vast volumes of data. The most obvious source of this data is the SCADA system itself. In the past, this data was only used for low-level diagnostics and was often not stored. Now, firms are using Big Data frameworks to store this data and are using offline analytics to look for patterns in the data. Other Big Data sources include billing data, CRM data, and third-party data sources. In addition, sensors are being added to meters and field service personnel are being equipped with handsets to monitor usage and performance in real-time. Email and social networks are also creating huge amounts of unstructured data.

These large data sets provide an incredible opportunity for greater insight and intelligence on business operations. However, this analysis is performed on Big Data “at rest” – that is, batch-oriented analysis of stored, historical data. By combining “at rest” analytics with the streaming data analytics provided by Vitria OI, energy and utilities firms have a formidable set of tools with which to tame the data deluge from both Big Data “at rest” and Big Data “in motion.”

Vitria OI provides the ability to correlate streaming data from real-time feeds and take immediate action on significant events. Where the same data is stored in a Big Data framework, Vitria OI can work alongside the Big Data store, providing the ability to replay past events, analyze those events for patterns, compare past events with the current situation, and employ patterns learned from offline analysis to the real-time feeds.

Once deployed, Vitria OI’s unified streaming analytics and action platform provides energy and utilities firms with continuous, real-time Operational Intelligence that benefits a wide variety of initiatives including those related to grid monitoring, customer care, and security programs.

Read more about how energy firms can benefit from streaming analytics