Advanced analytics and big data in Energy & Utilities
The amount of data that companies manage today is growing exponentially, while at the same time becoming more and more fragmented within the organization.
In this context, proper storage, processing, analysis, and visualization of this data brings real added value and enables the modern utility to fine-tune operations, support decision-making, development, and optimize infrastructure investments.
Often the traditional approaches of handling, analyzing and using the data are insufficient or impractical to use - this is where the modern big data approaches shine.
The implementation of advanced analytics and big data platform enables total control over the information, crucial for the utility company success.
With advanced analytics, utilities can improve network performance, increase reliability, reduce costs, and optimize other key performance indicators (KPIs) associated with power generation, transmission, and distribution.
Advanced analytics provides deeper and more detailed insights into all types of data and content, using advanced techniques and tools, that go beyond traditional analytical procedures. It includes areas such as data/text mining, machine learning, pattern matching, prediction, visualization, semantic analysis, sensory analysis, network and cluster analysis, multivariate statistics, graph analysis, simulation, complex event processing and neural networks.
The field of advanced analytics alone cannot be considered on its own, as the field is highly dependent on data collection and management, as well as on a specific industry. Within advanced analytics, several other areas and technologies are emerging, which also need to be considered in development. These areas are:
- Data management with a full set of technologies for BigData management (NoSQL, BigData, Data Lake, ELT/ETL, IoT...),
- Data visualization with the help of BI tools,
- Data mining with advanced analysis techniques
- Implementing advanced analytics using artificial intelligence and machine learning.
Big data is an organized collecting of data necessary for detailed analysis, followed by the identification of sample relationships between factors and based on the findings, making business decisions for the future of the company's operations. It is a set of data whose size, speed, or diversity exceeds the capabilities of traditional database management methods.