Do you want to know an example of big data and a specific industry it is used in? Or rather, what does big data mean? Big data refers to the data sets that can be processed and stored with speed, variety, and volume. One of the applications of big data is in the energy sector.
Currently, the use of energy is massive worldwide. Every process is somehow powered and supported by the energy sector. From businesses and factories to homes and schools, every sector of our society needs more energy today than ever before — and available at affordable prices. In the past, meeting such demand would have been an extremely complicated, if not impossible, task, but recent Big Data innovations have made it a reality.
Big Data is an important trend in modern companies as data has become the most relevant asset for many businesses. This innovative technology can be a critical resource you can rely on to make better business decisions. In the electrical industry, its use has increased exponentially in recent years.
Companies in the energy sector apply intelligent technologies to their services, including sensors, machine learning technologies, energy planning, and network communication. Es produces large datasets on an ongoing basis that are collected over time. And the greater the volume of data, the more complex it will be to perform an accurate and fast analysis.
In situations like this, Big Data’s value to accurate data analysis is evident. But this technology can be much more comprehensive, having interesting applications for several areas of the energy sector.
Example Of Big Data And Its Role In The Energy Sector
Risk analysis is one of the most exciting applications of this technology, and it is being used to solve complex business problems for making strategic investment decisions in the sector.
Energy companies use advanced analytics to filter their data collected from thousands of sensors and use it to make informed investment decisions. This data helps to assess market demand and provides all the necessary insights.
Power generation companies use advanced analytics and modeling to predict future prices and change their operating model to meet the challenges. When used in the cloud, Big Data enables information to be backed up and prevents business data from being lost in the future.
They allow energy companies to understand their portfolio risk profiles and potential opportunities, resulting in more strategic decisions.
Greater Efficiency In Monitoring
Energy companies seek to predict market changes using critical indicators in real-time to respond quickly and mitigate problems. With artificial intelligence, it is possible to incorporate and evaluate a large volume of information for energy companies. This allows them to prepare more effective trading strategies.
In this context, Big Data improves the monitoring and maintenance of equipment in the sector, minimizing production hours. When energy companies invest more in data to monitor their operation, they ensure that no future disaster or system failure could cost irreparable damage.
Data also improves machine efficiency. Sensors are being installed in the equipment to monitor its performance. All data collected is then analyzed and used for a collaborative business purpose. Better monitoring and oversight through data can allow energy producers to be more proactive.
Big Data technology has proven to be an essential catalyst for achieving the best commercial performance in the energy sector and is already paving the way for the industry’s future.
It is estimated that, due to the impact of global warming, air conditioning systems will consume 40% of electricity. As a result of possible demographic expansion in these countries, electricity consumption could almost double between 2025 and 2050.
A clear example of the application of these technologies is in the electricity grid environment. Thanks to IoT and 5G, billions of objects will be connected in this world, generating a large amount of data. Using data from generation, distribution, and consumption elements would improve grid management and energy savings.