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From Connected Data to Meaningful Visualisations Graph visualisations make complex data more accessible, but creating a meaningful graph visualisation is far from trivial. In this masterclass, we present a pipeline for transforming raw data into a visualisation that answers specific user questions. This class is designed for anyone working in data analysis, including data scientists, application developers, and researchers. We use free tools accessible to everyone. By the end of the masterclass, participants will have gained hands-on experience in transforming raw data into meaningful graph visualisations. Techniques of data analysis allow users to extract valuable insights from raw data. By exploring this data, they can answer specific questions, identify patterns, and make informed decisions. Graph visualisations enhance this process by making complex data more accessible. In this masterclass, you will discover how to transform raw data into meaningful graph visualisations, covering the entire pipeline from data to the final visualisation. First, we provide an overview of how to identify key questions that can be answered with graph visualisations. Then, using Jupyter Notebook—a popular and free tool for data analysts—and Neo4j databases, you will learn how to prepare data and apply graph analysis algorithms such as centrality and other relevant measures. Finally, you will explore how to select the appropriate visualisation style, focusing on what should be emphasised and how information can be effectively encoded in the visualisation. https://t.co/DmeVlryedl #DataViz #CDL24 #DataScience #GraphDB #Notebook #OpenSource #Masterclass #Tutorial #ConnectedData #visualization