The ecological and economical concerns for consumes reduction, the huge amount of data collected and the widespread of Machine Learning techniques have enhanced the employment of Artificial Intelligence methods as tools for optimal energetic management of facilities, for fault detection and consumes prediction. Many algorithms have been developed in the attempt of successfully deal with Big Data, with the perspective of supporting analysis, classifying elements and providing predictions and reference values. Time-serie analysis is an important field of application of Machine Learning algorithms, with specific features and constrains. Clustering of time-series, sub-sequences analysis, regression techniques, correlation analysis, decomposition and pattern discovery, development of appropriate prediction tools are some typical tasks regarding analysis of consumes.