The Viridis platform explores the concept of a data lake to combine time series sampled in real time with transactional data from management systems. To deal with large volumes of data, the system has a high-performance data historian with efficient storage and response times, capable of holding thousands of time series for many years. All this measurement data is combined with data from legacy systems such as ledger transactions, production orders, maintenance orders, laboratory data, among others. The system automatically correlates multiple types of data, temporal and transactional, allowing disruptive views on energy performance and operational efficiency.
Storing and processing large volumes of data is not a trivial task, especially when this information comes from multiple sources and is received in different formats. Different types of data, when combined, have the potential to influence strategic analyses and decision making, but they must be gathered and processed with agility and reliability.