Digital Cultural Heritage
Data cleaning is the process of identifying and correcting inaccuracies, inconsistencies, or errors in a dataset to improve its quality and reliability. This essential step ensures that data is accurate, complete, and usable, which directly impacts the effectiveness of data visualization efforts. Without proper data cleaning, visualizations can misrepresent information, leading to incorrect conclusions and poor decision-making.
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