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Best Practices for Data Visualization

The following reference article details how TeamConnect Report Designers can create the most effective reports to be leveraged by their teams. Best practices regarding the usage of tables versus graphs as well as effective report styles are detailed below with examples of scenarios for each data relationship type.
 Fundamental Steps in the Design Process
  1. Determine the message and intended audience.
  2. Select the best medium to display the message.
  3. Design the display to show information simply, clearly, and accurately.
  • Make the data (versus non-data) prominent and clear.
  • Remove all components that aren’t necessary (both data and non-data components).
  • Reduce the visual salience of the remaining non-data components in comparison to the data.
  • Highlight the information that’s most important to your message.
Pivot Reports

To resolve duplicate entries, any contact related reports need to be created as pivot tables.

In general, it's a good practice not to create a report with aggregation for pivot type reports. TeamConnect Business Intelligence sums the identifiers in these reports.

Using Tables vs. Graphs
Use Tables When Use Graphs When
The display will be used to look up individual values The message is contained in patterns, trends, and exceptions
The display will only be used to compare individual values rather than whole series of values Entire series of values must be seen as a whole and/or compared
Precise values are required  
Values involve more than one unit of measure
Values must be presented at various levels of aggregation (i.e. summary and detail)
 Graphs to Avoid

The graphs listed below demonstrate high visual impact but ineffective data communication.


Graphs and Data Relationships
  Points Lines  Bars
POINT.jpg LINE.png BAR.png

Time Series

Values display how something changed through time (yearly, monthly, etc.)

Yes (as a dot plot, when you don’t have a value for every interval of time)

Yes (to feature overall trends and patterns and support their comparisons)

Yes (vertical bars only, to feature individual values and to support their comparisons)


Values are ordered by size (descending or ascending)

Yes (as a dot plot, especially when the quantitative scale does not begin at zero)




Values represent parts (proportions) of a whole (for example, regional portions of total sales)


Yes (to display how parts of a whole have changed through time)



The difference between two sets of values (for example, the variance between actual and budgeted expenses)

Yes (as a dot plot, especially when the quantitative scale does not begin at zero)

Yes (when also featuring a time series)



Counts of values per interval from lowest to highest (for example, counts of people by age intervals of 10 years each)

Yes (as a strip plot to feature individual values)

Yes (as a frequency polygon, to feature the overall shape of the distribution)



Comparison of two paired sets of values (for example, the heights and weights of several people) to determine if there is a relationship between them

Yes (as a scatter plot)


Yes (as a table lens, especially when your audience is not familiar with scatter plots)


Values are displayed on a map to show their location

Yes (as bubbles of various sizes on a map)

Yes (to display routes on a map)


Nominal Comparison

A simple comparison of values for a set of unordered items (for example, products or regions)

Yes (as a dot plot, especially when the quantitative scale does not begin at zero)




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