Understanding Visualizations
Data visualization involves using visual images like graphs, charts, and pictures. Understanding visualizations used to present information in research is essential because is forms the basis of effective conclusions used in decision-making (Liu et al., 2018). Some of the visualizations the focus group research used include a newspaper picture and various types of graphs. These visualizations are vital because they help the focus group communicate their intended message to the audience efficiently.
With increasing dependence on data in the digital world, individuals need the ability to understand and interpret data, especially the one in large batches. Once of the concepts used to achieve this is machine learning, whereby it conducts analyses that can serve a useful visualizations. Although data visualization is associated with its benefits among data scientists and analysts, it is currently considered as a career that learners can pursue because visualizations are useful in all fields (Eigner, 2013).
Among the visualizations I chose is the three-dimensional graph presenting data about the usage of water resources in various countries and the newspaper photograph presenting information about Shakira’s influence through social media numbers. I chose these two visualizations because I found them easy to understand and comprehend. For instance, the graph enables an audience to assess which country is using more water resources than the other at a glance, thus saving time than it could be if the information was presented in written form.
Besides using less time to understand data, understanding visualizations helps in understanding trends and identify patterns presented in data. Visualizations ensure that the aim of data analysis is achieved by ensuring that learners and audiences can gain general insights, thus gaining the value of data. Additionally, with visualizations it is easy for researchers to present the true meaning of findings and ensure the targeted audience grasp this meaning.
References
Eigner, W. (2013). Current Work Practice and Users’ Perspectives on Visualization and
Interactivity in Business Intelligence. 2013 17th International Conference on Information
Visualization.
Liu, J. et al. (2018). A survey of scholarly data visualization. IEEE Access, 6.
10.1109/ACCESS.2018.2815030