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Wednesday, May 24, 2023

Waterfall Chart, Funnel Chart, Scatter Chart, Pie Chart, Donut Chart, Treemap Visuals


 The following dashboard uses the Sample - Superstore dataset to demonstrate the creation of:

  • Waterfall Chart
    • Waterfall chart visualizes positive and negative changes to a value or displays each individual component that contributes to the final value.
    • In waterfall chart there is a starting bar that represents the initial value then we have floating bars in space that represent positive and negative changes to that initial value. Lastly, an ending bar represents the final value and takes into account the effects of all the displayed transitional values.
    • The starting and ending bars both start with baseline of zero while the floating middle bars have their own baseline, which is the previous bar’s end.
    • In Power BI the following fields are shown in details pans:
      • Category specify a chart trend usually a time-based column e.g. year
      • Breakdown specify the column in which changes are required to be explored e.g. category
      •  Y-axis specify the numeric values that needs to be plotted e.g. sum of sales
  • Funnel Chart
    • Funnel chart visualizes progression or movement of data through different stages e.g. sales funnels, recruitment processes or order fulfilment processes.
    • It can be used when you have 3 or more stages to visualize and data diminishes at each stage.
    • In funnel chart the top most bar (aka “head” or “base” of the funnel) represents 100 percent data. The subsequent bars have lengths representing the proportion to the whole.
    • In Power BI the following fields are shown in details pans:
      • Category specify stages e.g. shipping mode
      • Values specify data e.g. total sales 
  • Scatter Chart
    • Scatter chart visualizes the relationship or association between two quantitative variables e.g. how does global oil prices affect a country’s GDP?
    • In Power BI the following fields are shown in details pans:
      • Values specify the categorical column e.g. sub-category
      • X-axis specify the horizontal-axis column e.g. sum of sales
      • Y-axis specify the vertical-axis column e.g. sum of profit
      • Legend specify which column to sub-divide the whole data e.g. category
      • Size specify column on the basis of which size of dots is defined e.g. sales
      • Play axis specify the column for trend over time usually a date column
  • Pie Chart
    • Pie chart displays categorical data in a circular graph. The entire “pie” represents 100% of a whole, while the pie “slices” represent portions of the whole.
    • Primary objective of a pie chart should be to compare each group’s contribution to the whole.
    • In Power BI the following fields are shown in details pans:
      • Legend specify which column to sub-divide or slice the whole data e.g. category
      • Values specify the numerical column e.g. sum of sales
      • Details specify further column to sub-divide or slice the data
  • Donut Chart
    • Donut chart is a pie chart with its center cut out to look like a donut.
    • In Power BI the following fields are shown in details pans:
      • Legend specify which column to sub-divide the whole data e.g. category
      • Values specify the numerical column e.g. sum of sales
      • Details specify further column to sub-divide or slice the data
  • Treemap
    • Treemap chart displays large amount of hierarchical data using rectangles of decreasing sizes.
    • Rectangles in the treemap are arranged according to size.
    • Tree map visualize a part-to-whole relationship among a large number of categories.
    • A pie chart might best work with three or fewer segments, a treemap works well with many.
    • In Power BI the following fields are shown in details pans:
      • Category specify the categorical column and define structure of the treemap e.g. sub-category
      • Values specify the numeric column and define size or color of the individual rectangles e.g. sum of profit
      • Details specify further column to sub-divide the data



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