This project was a teaching presentation that explored the fundamentals of data visualisation. It started with the core question: why do we visualize data at all? The talk laid out multiple answers: to help communicate actual data or predictions or facilitate understanding trough simulations, storytelling and visualised algorithms. A central case study was the spaghetti chart problem, which describes overloaded line charts where individual patterns are impossible to distinguish. I used this example to show how poor design obscures meaning, and then introduced better approaches such as small multiples, highlighting, filtering, and combinations of these methods. The presentation also covered the importance of visual encodings (position, color, size, shape) and how they should be chosen. It moved into modern features such as interactivity and animation, and finally discussed the role of human perception, referencing Gestalt principles and design heuristics that explain how people interpret visual patterns.