Data Science

Diving deep into Data Visualization. A look at some applications & techniques

In this blog, we will take you through a few data visualization techniques and its varied applications.

Below are a few commonly used data visualization techniques:

Infographics: This is a technique of using a distinct collection of images, words, and charts to create a comprehensive and easy to understand display of data.

Scatter Plots: A visualization technique where two variables are plotted on the x and y axis with an established correlation.

Fever Charts: This visualization technique is popularly used in the stock markets to track continuously changing prices over time.

Population Pyramids: These help in illustrating population distribution through a stacked bar graph.

So, these were a few popular techniques of data visualization, let's now look at how these techniques are implemented in various domains.
  • Useful in determining a correlation between any two variables plotted.
  • Examining a network of audiences and bridging variables to arrive at meaningful insights in statistical behaviour.
  • Examining and tracking trends over a period of time.
  • Determining the pulse and frequency of changes and how often they occur.
  • Data visualization for tracking investments in commodities and stocks.
  • Monitoring and predicting healthcare patterns.
  • Determining optimum shipping routes for logistics.
  • Understanding research data to give meaningful insights into Research & Development


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