As climate datasets grow in complexity and volume, researchers require efficient, scalable, and user-friendly tools to analyze and visualize geospatial data. The ENES Data Space (https://enesdataspace.vm.fedcloud.eu) offers a cloud-based data science environment for climate data analysis built on top of the European Open Science Cloud (EOSC) Platform. More specifically, it provides direct access to pre-configured computational resources, analytical tools, and climate datasets without the need for local installations and data transfer.We will demonstrate how MATLAB Online (https://uk.mathworks.com/products/matlab-online.html), integrated within the ENES Data Space, enables seamless climate data exploration, by importing diverse climate datasets, including historical observations and future projections, directly into MATLAB Online. We will highlight interactive data selection and visualization techniques, including dynamic mapping and comparative analysis, showcasing MATLAB’s intuitive Live Scripts for an accessible, code-light workflow.A key focus will be on leveraging parallel computing within MATLAB to accelerate data processing, particularly for large-scale geospatial datasets. By running computations across multiple cores directly in the cloud, users can enhance performance without requiring specialized hardware. The demonstration will also explore exporting results in multiple formats, facilitating collaboration and reproducibility.This presentation aims to illustrate how MATLAB in the ENES Data Space simplifies climate data analysis through interactivity, efficiency, and scalability—empowering researchers, educators, and students to extract insights with ease.