Energy data analytics blog

The IoT (internet of things) is a concept that refers to a digital interconnection of everyday objects with the internet, that is, physical objects that carry integrated sensors to collect data and thanks to this, in some cases, they can also interact. 

Big data analysis tools have the ability to handle large volumes of data generated from IoT devices that create a continuous flow of information in real time.

IoT provides the necessary data to be able to perform big data analysis and extract information that generates the required perceptions.

The processes to follow to work on an analysis of energy data using Big data and IoT are the following:

Mainly, real-time measurement, control and analysis of energy performance in a manufacturing company is carried out, supported by consumption, performance and energy saving indicators.

The use of both technologies makes operational processes more efficient in all sectors of the energy value chain. Ideally, the systems that have these advanced data processing tools allow users to create real-time Analysis sessions in an agile and intuitive way.

Big Data technology is capable of offering useful and strategic information for the business from a detailed and advanced analysis of the captured information. It offers a powerful tool that allows you to analyze energy demand in depth, betting on a personalized energy model for each consumer and, therefore, more efficient and sustainable.

With BIG DATA technology, the aim is to characterize the energy consuming profiles, predicting their behaviors based on all the environmental variables that have a significant influence on their consumption.

BIG DATA technology also provides a key and strategic value in the rest of the agents in the value chain, UTILITIES (Electricity, Gas, Water and Renewable Energy companies sector) can rely on BIG DATA technology to optimize production in business, transport processes, energy distribution and thus even modify consumption habits in customer profiles (energy consumers), which translates into greater efficiency, lower costs and reduced environmental impact.

An operational intelligence platform based on Big Data technology must basically make up this loop:


Having these tools integrated into a platform, using both technologies, it is necessary to analyze the information obtained, create new strategies from said information, know how it is consumed and why it is consumed, establish patterns of it, analyze the environment (economic, social and environmental) and how it influences our energy consumption patterns.

The Internet of Things (IoT) is moving towards a future in which smart sensors can detect the environment they are in. That flow of data between devices is what makes Big Data systems meaningful.

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