Big data visualization represents complex data and sets in an easy-to-understand manner without sacrificing accuracy. This allows users to draw accurate and dependable conclusions from the data, which can reliably inform the decision-making process for decision-makers.
Identifying the correlation of events
Big data is often stored in an unstructured data format or in a tabular configuration in a program like pandas DataFrame. It can combine various data sources, including text, images, audio, and video. This can make it difficult to compare the various types of large amounts of data against each other to identify patterns and correlations.
Using big data visualization lets you read and understand disparate data sources together, and you can explore data sets so analysts can more easily identify any correlation of events across various types of data.
Big data visualization tools often operate in real-time, collating, refining, and presenting data rapidly following its generation. This means that any user accessing big data visualization tools receives up-to-date and relevant data, allowing them to make well-informed decisions and react to changes quickly as they happen
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