Huge amount of multivariate time series (TS) data are recorded by helicopters in operation, such as oil temperature, oil pressure, altitude, rotor speed to mention a few. Despite the effort deployed by Airbus Helicopters towards an effective use of those TS data, getting meaningful and intuitive representations of them is a never ending process, especially for domain experts who have a limited time budget to get the main insights delivered by data scientists. In this paper, we introduce a simple yet powerful and scalable technique for visualizing large amount of TS data through patterns movies. We borrow the co-occurrence matrix concept from image processing, to create 2D pictures, seen as patterns, from any multivariate TS according to two dimensions over a given period of time. The cascade of such patterns over time produces so-called patterns movies, offering in a few seconds a visualisation of helicopter' parameters in operation over a long period of time, typically one year. We have implemented and conducted experiments on Airbus Helicopters flight data. First outcomes of domain experts on patterns movies are presented.