Data visualization offers a myriad of ways to represent data, each suited to different kinds of data and the specific insights one wishes to convey. Below are some of the most common types of data visualizations:
- Bar ChartRepresents categorical data with rectangular bars where the lengths are proportional to the values they represent. They can be horizontal or vertical.
- Pie ChartA circular chart divided into slices to illustrate numerical proportions. Each segment represents a category’s portion of the whole.
- Line ChartDisplays information as a series of data points connected by straight line segments. Ideal for showing data trends over time.
- Area ChartSimilar to a line chart, but the area between the axis and the line is filled with color or shading, representing volume.
- Scatter PlotUses dots to represent two variables’ values, where one variable is on the x-axis and the other on the y-axis. Useful for showing the relationship between two sets of data.
- HistogramA bar chart that groups numbers into ranges, showing the distribution of a dataset.
- Heat MapRepresents data values in a two-dimensional space, where values are denoted by varying color shades or intensities.
- Choropleth MapUses different shades or patterns within predefined areas (like countries or states) to indicate value levels.
- Bubble MapUses circles of varying size and color at specific geographic locations to represent data values.
- Description: Infographics combine visuals, charts, text, and icons to tell a narrative, often used to explain complex data simply or to tell a data-driven story.
- Applications: Infographics can be used for comparing data, explaining processes, showing a timeline, or presenting survey results, among other things.
- Description: A dashboard is a single screen that aggregates multiple visualizations, giving an overview of important metrics and performance indicators.
- Applications: Dashboards are commonly used in business intelligence to monitor business processes, track KPIs (Key Performance Indicators), or provide a snapshot of organizational health.
- Description: These are dynamic visualizations that allow users to interact with the data, often using features like zooming, filtering, and drilling down for detailed views.
- Applications: Interactive visualizations are prevalent in digital platforms where stakeholders wish to explore data, perform ad-hoc analysis, or understand intricate relationships within datasets.
In essence, the choice of visualization type depends on the nature of the data and the specific insights one aims to convey. The right visualization not only enhances understanding but also engages the audience, turning data into a compelling story or actionable insight.
Key terms in plain language
Open a term for a concise explanation of language used on this page.
Broadband
A general term for always-on, high-speed Internet access. Broadband can be delivered over fiber, cable, DSL, fixed wireless, cellular, or satellite networks.
Cloud Computing
Computing resources—such as applications, servers, storage, or databases—delivered from remote infrastructure and scaled as requirements change.
Cybersecurity
The practices and controls used to protect identities, devices, networks, applications, and data from unauthorized access, disruption, or manipulation.
Identity and Access Management (IAM)
The systems and policies that determine who a user is, what resources they may access, and how that access is authenticated and reviewed.
API
An application programming interface is a defined way for software systems to exchange data or request functions from one another.
Artificial Intelligence (AI)
Software designed to perform tasks involving prediction, classification, generation, reasoning, or decision support. Business use still requires clear data, governance, security, and human accountability.