How does visualization of big data help in interpreting information?
Answers
Answer:
Data visualization is the practice of translating information into a visual context, such as a map or graph, to make data easier for the human brain to understand and pull insights from. The main goal of data visualization is to make it easier to identify patterns, trends and outliers in large data sets.
Explanation:
Data visualization is the process of transforming information into a visual context, such as a map or diagram, so that the human brain can more easily understand and understand it. The main purpose of data visualization is to facilitate the identification of patterns, trends and anomalies in large data sets. The term is often used interchangeably with others, including data graphics, data visualization, and statistical graphics.
Data visualization is one of the steps in the data science process, which states that after data is collected, processed and modeled, it must be visualized to draw conclusions. Data visualization is also part of a broader Data Presentation Architecture (DPA), which aims to identify, find, process, format and communicate data in the most efficient way possible.
Data visualization is important to almost every career. It can be used by teachers to display student test results, computer scientists studying advances in artificial intelligence (AI), or managers looking to share information with stakeholders. It also plays an important role in big data projects. In the early years of the big data trend, companies collected huge amounts of data, so they needed a way to get information about their data quickly and easily. Visualization tools are a natural fit.
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