In this paper, we have described cloud data and its source, as well as the technologies and application used for processing this data. The satellite images used in the study were obtained from the European Organization for Meteorological Satellites (EUMETSAT). The Meteosat series satellites are positioned in geostationary orbit above the Earth, enabling continuous monitoring of a specific area. The coverage area ranges from -67.5 to 67.5 degrees of latitude and longitude. Satellite images are regularly refreshed every 15 minutes, and the data is packaged in the GRIB format, which is a standard format for storing meteorological data. Each coordinate on the images is marked with values ranging from 0 to 3, representing different weather conditions. In the second part of the study, we describe the application used for processing this data. The application consists of a web application and a Python script. The web application allows for selecting a specific time frame and displaying the data on a 3D globe using Cesium. The Python script, on the other hand, opens GRIB files, processes the data, and saves it in JSON format. As fundamental technologies, we utilize Node.js for developing web applications and Python for data processing. Node.js is an open-source server environment that executes JavaScript outside of a web browser, while Python is a general-purpose programming language that offers flexibility and popularity.