https://video.osgeo.org/videos/watch/f55d7e82-f9ab-470a-b04d-275815b49f56 Handling "big data" (large volumes of data) primarily generated by automated weather stations and their installed sensors, requires special attention across the processes of data collection, processing/transformation, storage, presentation, and delivery. The first step is identifying data sources and selecting appropriate access methods. Next comes data transformation, which depends on the data type and the relational database model (RDBMS) into which we plan to transfer it using adequate ETL tools. A critical aspect is ensuring the storage model accommodates heterogeneous sources while remaining efficient for access and delivery. The final step involves interfaces, either machine-based (API) or user-based (UI), that enable seamless data access and consumption. Challenges increase significantly when dealing with spatial data, which comes in various forms, including numerical measurements, raster satellite imagery, radar images, and numerical forecasting models. Each stage demands thorough planning and optimization to handle billion-record tables and terabytes of raster data effectively. In this presentation, we will share our experiences in managing large datasets from diverse location and weather sensors, as well as spatial imagery, highlighting the complexities of processing and visualizing data. Igor Karuza https://talks.osgeo.org/foss4g-europe-2025/talk/UA9CRS/ Room: SA02 @ 16.07.2025 15:00:00 #foss4ge2025 #GeneralTrack #UseCasesApplications Tue, 04 Aug 2026 16:40:31 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://video.osgeo.org https://video.osgeo.org/lazy-static/avatars/de841c88-3a57-45ac-9eff-a00237356bfc.png https://video.osgeo.org/videos/watch/f55d7e82-f9ab-470a-b04d-275815b49f56 All rights reserved, unless otherwise specified in the terms specified at https://video.osgeo.org/about and potential licenses granted by each content's rightholder.