Explanation:
Data visualization comes in a variety of forms. Scatter plots, line graphs, pie charts, bar charts, heat maps, area charts, choropleth maps, and histograms are among the most frequent.
Explanation:
The graphical depiction of information and data is known as data visualization. Data visualization tools make it easy to examine and comprehend trends, outliers, and patterns in data by employing visual elements like charts, graphs, and maps.
Explanation:
A graphical depiction of information and data is known as data visualization. Data visualization tools make it easy to examine and comprehend trends, outliers, and patterns in data by employing visual elements like charts, graphs, and maps.
Explanation:
The ability to track links between operations and overall business performance is one of the advantages of big data visualization. In a competitive climate, establishing a link between corporate activities and market success is critical.
Explanation:
Data visualization is part of the broader data presentation architecture (DPA) discipline, which strives to efficiently identify, find, modify, prepare, and transmit data. Almost every occupation requires data visualization.
Explanation:
This is an intricate technique that is not used in data visualization.
Explanation:
While the strategies are some of the most prominent, there are many other ways to display data to improve your communication skills.
Explanation:
Treemapping is a method for showing hierarchical data using nested figures, usually rectangles, in information visualization and computing. Treemaps are a group of nested rectangles that represent hierarchical (tree-structured) data.
Explanation:
With dynamic visual representations of data, data visualization has a positive impact on an organization's decision-making process. Because they can analyze data in graphical or pictorial representations, businesses can now recognize trends more quickly.
