Workspace/Foundations/Data visualization

Types

Choose the appropriate data visualization for your intended purpose, user, and use case.

Comparison

Comparison charts display variations and similarities in data.

Use case examples:

  • Customer Satisfaction
  • Social Media Growth

Chart types:

Data vis horizontal bar chart representing incidents vs priority

Horizontal bar: A horizontal bar chart visually compares data using horizontal bars. It's great for quickly identifying the largest or smallest values in different categories.

Data vis vertical bar chart representing category vs number of open incidents

Vertical bar: A vertical bar chart visually compares data using vertical bars. It's effective for quickly identifying the largest or smallest values in different categories.

Data vis bubble chart representing incident cost vs business resolve time

Bubble: A bubble chart is a visual representation of data using bubbles of different sizes. It displays data on both the x and y axes, with the size of each bubble representing a third variable. This chart type is useful for showing relationships between three different variables and allows for easy identification of patterns or outliers. The position of each bubble on the chart indicates its x and y values, while the size represents the magnitude of the third variable.

Trend

Trend charts display information that has undergone transformations throughout a period of time.

Use case examples:

  • Stock Prices Over Time
  • Website Traffic Trends

Chart types:

Data vis line chart representing different stock prices over months

Line: A line chart is a type of chart that displays data using a series of data points connected by straight lines. It is commonly used to show trends or changes in data over time or other continuous variables. Line charts are effective in visualizing the relationship between two variables and identifying patterns, fluctuations, or correlations. 

Data vis spline chart representing number of open incidents over months

Spline: A spline chart is a type of chart that is similar to a line chart, but the lines are smoothed using a mathematical function called a spline. This smoothing technique helps to reduce the jaggedness of the lines and provides a more visually appealing representation of the data. Spline charts are commonly used to display trends or changes in data over time or other continuous variables, just like line charts. The smooth curves of the lines make it easier to identify patterns and trends in the data, especially when there are fluctuations or irregularities. 

Data vis area chart representing a stock price over months

Area: An area chart is a type of chart that displays data using filled areas between lines. It is similar to a line chart, but the area below the line is filled with color or pattern. Area charts are useful for showing the cumulative totals or proportions of different categories over time or other continuous variables. 

Data vis column chart representing two different stock prices over months

Column: A column chart is a type of chart that displays data using columns or bars.

Data vis step chart representing two different stock prices over months

Step: A step chart, also known as a step plot or a step line chart, is a type of chart that displays data using a series of horizontal and vertical lines. It is commonly used to show changes in data over time or other continuous variables, similar to a line chart. However, unlike a line chart where the data points are connected by straight lines, a step chart connects the data points using horizontal and vertical lines that create a step-like appearance.

Part to whole

Part-to-whole charts display the sum of partial components in relation to the whole.

Use case examples:

  • Budget breakdown
  • Website traffic sources

Chart types:

Data vis pie chart representing different proportions of incident priorities

Pie: A pie chart is a circular chart that represents different categories or proportions of a whole. Each slice corresponds to a category, and its size indicates the proportion it represents. Pie charts are useful for comparing proportions, but it's not recommended to use more than 5 or 6 slices as they can become difficult to interpret.

Data vis donut chart representing proportions of different categories of incidents

Donut: A donut chart is a variation of a pie chart with a hole in the center. It displays the same type of data as a pie chart, showing proportions or percentages of a whole. The outer ring of the donut chart represents the total, while the slices represent different categories. Like pie charts, it’s not recommended to use more than 5 or 6 slices in a donut chart for clarity and ease of interpretation.

Data vis semi donut chart representing proportions of incident priorities

Semi donut: A semi-donut chart, also known as a half-donut or a half-pie chart, is a variation of a donut chart that displays data in a half-circle shape. Like pie charts, it is not recommended to use more than 5 or 6 slices in a donut chart for clarity and ease of interpretation.

Data vis stacked bar chart representing proportions of multiple incident categories

Stacked bar: A stacked bar chart is a type of bar chart that displays multiple categories or subcategories as stacked bars within each main category. Each bar represents the total value of the main category, and the different segments within the bar represent the proportions or values of the subcategories.

Data vis stacked area chart representing number of incidents in IT vs sales

Stacked area: A stacked area chart is a type of chart that displays the cumulative values of multiple categories or variables as stacked areas. Each area represents the total value of the category or variable at a given point in time or along an axis.

Data vis gauge chart representing number of open incidents

Gauge: A gauge chart is commonly used to represent metrics such as progress, performance, or levels of achievement. The chart typically consists of a circular scale with labeled intervals or ranges, and a needle or pointer that indicates the value being measured. There are 2 style variants: 180 and 240.

Data vis dial chart representing a percentage

Dial: A dial chart, also known as a radial chart or circular gauge, is a type of chart that represents data using a circular dial or gauge. It is similar to a gauge chart but typically does not have a needle or pointer.

Correlation

Correlation charts display the association between two or more variables.

Use case examples:

  • Exercise frequency vs. Weight
  • Video game difficulty vs. Player engagement

Chart types:

Data vis scatter chart representing incidents across dates

Scatter: A Scatter chart is particularly useful for examining the correlation or relationship between two variables. The pattern or trend of the data points on the chart can provide insights into the strength and direction of the correlation.

Data vis heat map chart representing incident priorities and their categories

Heat map: A heatmap is a type of chart that uses color to represent the magnitude or density of values within a matrix or table. It is particularly useful for visualizing large datasets and identifying patterns or trends within the data.

Geospatial

Geospatial data visualization display information that is related to geographic locations or spatial relationships.

Use case example:

  • Sales performance in a country divided by districts, cities, etc.

Chart type:

Data vis geo map chart representing number of incidents in different states

Geo map: A geo map, also known as a choropleth map, is a type of map that uses color or shading to represent data values for specific geographic regions. It is a powerful visualization tool for displaying spatial patterns and variations in data across different areas or regions.

Tabular

A tabular chart, also known as a table, displays data in a structured format with rows and columns.

Use case examples:

  1. Identify trends in employee performance by department and experience level.
  2. Analyze customer support tickets by issue type and agent to identify areas for improvement.

Chart types:

Data vis pivot table representing a dataset covering assignment groups, incident counts, and problem counts

Pivot: A pivot table is to summarize and analyze large datasets. It allows you to rearrange and aggregate data based on different variables, providing quick insights and answers to specific questions.

Data vis indicator scorecard representing a dataset of indicator source, score, percentage change, target, and trend

Indicator scorecard: An indicator scorecard is helpful in visualising an indicator source, aggregating, grouping its data and identifying latest score, the change, gap, trend and target.

KPI

A key performance indicator (KPI) is a measurable value that helps organizations track and evaluate their progress towards achieving specific goals or objectives.

Use case example:

  • To understand the number of open incidents and their related target, gap, and change analysis.

Chart types:

Data vis single score chart representing a metric KPI

Single score: A single score displays a score with an accompanying icon to represent the current score of a source when the data was collected or a job was run. It also includes information on the change, target, and gap. Additionally, it features a trend preview in the form of a line, with a target line for reference. This visualization provides a concise summary of the source's performance and its progress towards the target.

Pareto analysis

Pareto analysis is a technique used to identify and prioritize the most significant factors or issues that contribute to a problem or outcome

Use case examples:

  1. In quality improvement, identify the 20% of defects causing 80% of issues.
  2. In inventory management, focus on the 20% of top-selling products generating 80% of revenue.

Chart types:

Data vis pareto chart representing priority vs number of incidents in a vertical bar chart and its percentage trend in a line chart

Pareto: A Pareto chart is a visual tool that combines a bar chart and a line graph to display data in descending order of importance. It helps identify the most significant factors contributing to a problem or outcome. The bars represent the frequency or magnitude of each category, while the line graph shows the cumulative percentage. This chart allows for quick analysis and prioritization of issues based on their impact.