RESPOND TO POST BELOW with in-text citations and references

A distinguished statistician, John Tukey, said "The greatest value of a picture is when it forces us to notice what we never expected to see." Rather than describing the dataset visualization techniques can be used. Visualization helps us to discover new angles on data, to visualize patterns, observe patterns and exceptions. Not only graphs and charts store quantitative information, but they also communicate conclusions and discover new information (Kirk et al., 2016).

The most common types of data visualization are: column chart, line graph, pie chart, bar chart, heat maps, scatter plot, bubble chart, funnel chart, radar chart, tree chart, flow chart, gauge, Gantt chart, Venn diagram, histogram, waterfall chart, Marimekko Chart, Choropleth Map, PERT Chart, dichotomous key, mind map, timeline, concentric circles, radial wheel, donut chart, half-donut chart, percentage bar, polar graph, icon array, cone chart (Simplileran, 2023).

Consolidating data visually allows us to perceive data easier. The data contains quantitative measures and visualizing data simplifies analysis without the need of additional explanation. Here we can see that romance is the most popular type of movie where drama is the least popular one. Action is the second favorite movie type. And comedy and SciFi have the same ratings. Visualizing data allows us to identify patterns, compare findings and evaluate dataset all in one.