Here are several data visualization techniques for presenting qualitative data for better comprehension of research data. As humans can process visual images better than texts, data visualization techniques enable viewers to remember them for a longer time.ĭifferent Types of Data Visualization Techniques in Qualitative Research.Allows the presenter to narrate a story whilst helping the viewer understand the data and draw conclusions from it.Illustrations make it easier to identify correlated parameters.Enables viewers to recognize emerging trends and accelerate their response time on the basis of what is seen and assimilated.Moreover, in this age of Big Data, visualization can be considered an asset to quickly and easily comprehend large amounts of data generated in a research study. Human eyes are often drawn to patterns and colors. What Are the Advantages of Good Data Visualization Techniques?Įxcellent data visualization techniques have several benefits: Unlike quantitative data, qualitative data cannot be expressed in continuous integer values it refers to data values described in the non-numeric form related to subjects, places, things, events, activities, or concepts. Quantitative data expresses the size or quantity of data in a countable integer. What Is the Importance of Data Visualization in Qualitative Research?Īccording to the form in which the data is collected and expressed, it is broadly divided into qualitative data and quantitative data. Hence, this technique is adopted to help presenters communicate relevant research data in a way that’s easy for the viewer to interpret and draw conclusions. It is imperative to think beyond numbers to get a holistic and comprehensive understanding of research data.
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