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Data Visualization as a Catalyst in Decision-making

Man holding a screen with virtual images of data visualization

Making use of data for better decision-making is largely dependent on the way the available data is perceived by the analyst. Data visualization is an essential tool for businesses to analyze and understand data more efficiently. Traditional techniques like lengthy tables and numbers are not only time-consuming and confusing, but also limit the analyst’s capabilities to make better decisions. Visual representations of data can help decision-makers identify patterns, trends, and outliers that might not be visible in raw data.

Barring the usual line charts and pie diagrams, here are a few data visualization tools that can help you get a better understanding of your data:

Scatter Plots

A scatter plot is a type of data visualization used to display the relationship between two variables. Scatter plots are particularly useful for identifying patterns, trends, and correlations between variables. By visualizing the relationship between two variables, decision-makers can gain insights into how changes in one variable affect the other variable. Scatter plots can be used in various industries, such as finance, marketing, and healthcare, to analyze and interpret data.

Heat Maps

Heat maps are commonly used to represent large data sets, and each data point is represented by a color-coded cell. The intensity of the color used to represent the data point indicates its value. Heat maps can be used to identify patterns and trends in data, making them useful in data analysis. Heat maps can be used to identify areas of high activity, customer behavior, or to identify trends in the market. Heat maps are an effective way of visualizing large datasets as they allow for quick identification of trends and patterns.

Tree Maps

Tree maps are a type of data visualization that displays hierarchical data sets as a set of nested rectangles. The size of each rectangle corresponds to the value of the data set. The rectangles are color-coded to represent different categories or subcategories. Tree maps can be used to represent organizational structures, website navigation, or file systems. By visually representing the data, decision-makers can quickly understand the relationship between categories and subcategories. This can help identify areas for improvement or optimization. Tree maps are particularly useful for visualizing large hierarchical data sets, as they provide an intuitive way to navigate and understand the data.

Sankey Diagrams

Sankey diagrams are a type of data visualization that displays the flow of data or resources between different categories. The width of the lines in the diagram represents the quantity or volume of the data or resources being transferred. Sankey diagrams are commonly used to represent energy consumption, customer behavior, or financial transactions. By visually representing the flow of data or resources, decision-makers can quickly understand the relationship between different categories and identify areas for improvement or optimization. Sankey diagrams are particularly useful in identifying inefficiencies in processes or systems.

 

With the growing amount of data generated by businesses, effective data visualization is more important than ever. Moreover, data visualization enables decision-makers to make informed decisions based on insights gained from data analysis. By visually representing data, decision-makers can quickly understand the relationship between different variables and identify areas for improvement.

If you want help to improve on your data visualization techniques and introduce better tools within your organization, you can get in touch with our Saransh experts at info@saranshinc.com.

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