Visualizations in Planning Analytics Workspace Classic

You can use any of the visualizations that are described here to present data in Planning Analytics Workspace Classic.

View this video to learn how to build visualizations in Planning Analytics Workspace Classic.

Video that demonstrates the use of the intent bar and snap commands to edit views.

https://youtu.be/d2GlvVDpwxE

To change the way data is presented, click a view, and then click Shortcut bar. Then, click the Change visualization icon Change visualization icon.

The visualizations available vary according to the dimensionality and configuration of your view. The Change visualization list contains only the visualizations that can be rendered with your current view configuration. For an accounting of which visualizations are available for specific view configurations, see Visualizations available by view configuration.

When you create a visualization, columns are always used as measures, while members on the row dimensions are visualization categories.

A visualization displays only as many columns of data as the number of measures it supports. For example, a Stack Bar (1 measure) visualization displays only the first column of data and ignores all other columns. Similarly, a Line and Column (2 measure) visualization displays only the first two columns of data and ignores any remaining columns. Details on the number of measures that are supported for specific view configurations can be found in Visualizations available by view configuration.

If you click on a visualization member, you'll see several options to interact with the visualization.

Visualization member showing
Drill down
Reveal the members of a consolidation. You cannot drill down on a leaf member.
Drill up
Collapse the member to show its immediate parent.
Hide
Hide the member in the visualization.
Unhide all
Reveal all hidden members in the visualization.

The following visualizations are available in Planning Analytics Workspace:

Area
An area visualization emphasizes the magnitude of change over time.
Because an area visualization stacks the results for each column or item, the total of all results is easily seen.
For example, an area visualization is excellent for looking at revenue over time across several products.
Bar
A bar visualization uses horizontal bars to show the values in individual groups or categories. The length of a bar indicates each value. Bar visualizations are useful for comparing values.
For example, a bar visualization might show the number of males and females who purchased a specific item. The length of one bar would show the number of males, and the length of the other bar would show the number of females. By checking the length of the bars, you can easily compare the values in the groups or categories.
Bubble
A bubble visualization shows relationships among columns that contain numeric values, such as revenue and profit.
The bubbles are in different sizes and colors. The x-axis represents one measure, the y-axis represents another measure, and the size of the bubbles represents the third measure.
For example, a bubble visualization shows cost in the x-axis, revenue in the y-axis, and quantity sold for all products. There is one bubble for each product. The location of the bubble in the visualization indicates the product's cost and revenue. The size of the bubble indicates the quantity sold.
Because a bubble visualization uses area to represent numbers, it is best for positive values. If your data set includes negative values, they are shown in a different color: a circle for 100 and a circle for -100 will both be the same size, but 100 might be blue and -100 might be red. If your data set has many negative numbers, consider that uses a bar visualization.
Column
A column visualization uses vertical bars to show the values in individual groups or categories. The height of a bar indicates each value. Column visualizations are useful for comparing values.
For example, a column visualization might show the number of car models sold in a region. The height of one bar would show the number of one car model, and the height of another bar would show the number of a different model. By checking the height of the bars, you can easily compare the values in the groups or categories.
Exploration
An Exploration shows data in rows and columns using a grid-style layout.
Heat
A heat map visualization shows the relationship between columns, using color and intensity.
Line
A line visualization shows trends over time.
A line visualization can compare trends and cycles, infer relationships between variables, or show how a single variable is performing over time.
For an effective line visualization, the x-axis should show time, such as years, quarters, months, or days. If the x-axis shows something else, such as individual countries, use a bar visualization instead.
Line and column
Display requirements: a defined measures dimension with two members.
A line and column visualization shows values for two measures, with one measure represented by columns and the other measure represented with a line.
List
A list visualization displays values in a list ordered first by row members, and then by column members.
Map
Display requirements: a defined geography dimension on the row axis of your view.
A map visualization shows patterns in your data by geography.
Your data set must contain geographical data, such as countries, states, or provinces. To determine if a dimension is mappable, Planning Analytics Workspace analyzes a sample of 2000 values in the row dimension, looking for recognizable place names. If 80% or more of the members in the geography dimension are recognized as map values, a map is generated.
For example, you have four countries in your geography dimension: Brazil, China, Indai, and Russia. The misspelling of India means that only 75% of the values are recognizable place names and you cannot generate a map.
For more information on the languages and geographic entities supported in map visualizations, see Map reference info.
For details on configuring a view to display a map visualization, see Create a map visualization.
Packed bubble
A packed bubble visualization shows relationships among columns that contain numeric values, such as revenue. It's a good choice when you want to display a large amount of data in a small space.
The bubbles are in different sizes and colors.
Because a packed bubble visualization uses area to represent numbers, it is best for positive values. If your data includes negative values, they display in a different color: a circle for 100 and a circle for -100 are both the same size, but 100 might be blue and -100 might be red. If your data has many negative numbers, consider using a bar visualization.
Pie
A pie visualization displays values as segments of a circle, or as slices of a pie.
Point
A point visualization uses multiple points to show trends over time. It is similar to a line chart, but without the lines; only the data points are shown.
Radial
A radial visualization displays values as segments of a single ring. The length of a segment in the ring indicates value.
Radial bar
A radial bar visualization displays values as concentric rings of a circle. It's similar to a standard bar chart, but the bars are bent into a circular shape.
Stack bar
A stack bar visualization is similar to a regular bar visualization, but instead of grouping values next to each other and displaying individual bars, values are placed in a single bar and positioned end-to-end. The length of a segment in the bar indicates value.
Stack column
A stack column visualization is similar to a regular column visualization, but instead of grouping values side-by-side and displaying individual columns, values are placed in a single column and positioned on top of each other. The height of a segment in the column indicates value.
Tree map
A tree map visualization identifies patterns and exceptions in a large, complex data set.
Tree maps show relationships among large numbers of components by using size and color coding in a set of nested rectangles.
A tree map that is colored by category identifies the level 1 category by color. The sizes of the rectangles represent the values. In a tree map that is colored by value, the sizes of the rectangles represent one of the values and the color represents a second set of values. Do not use data that includes negative numbers. A tree map ignores negative numbers.
Word cloud
A word cloud visualization presents a visual representation of text values. The more frequently a text string occurs in your data, the larger the string appears in the word cloud.