The MariData project was recently launched to improve the energy efficiency of ship operations and to reduce emissions. Fuel consumption regarding vessel traffic is affected by many factors, namely, the main and auxiliary engines, the propulsion system, ship hull, propellers, seakeeping performance, as well as weather and sea conditions. In order to tackle these problems, we divide the task of building a weather routing system into subproblems and handle each subproblem separately. Finding the correlations between the speed of the vessel and weather conditions would lead to a better understanding of the weather conditions affecting fuel consumption, therefore, we obtained speed data of the ship’s Automatic Identification Systems (AIS), then retrieved weather and sea information for each data point using timestamp and geographic locations. The combination of these data sources enabled us to build a model to better understand the inherent relationships.