There’s a lot that can be gained by pouring over dense pages of research, or individually looking at sets of data. In fact, the most successful individuals and companies often spend a lot of time doing both of these things. Fortunately for those who aren’t eager to spend hours on end parsing through esoteric jargon and numbers, data visualization makes the process a whole lot easier.
It’s no secret that data is crucial for businesses, which is why the biggest, most successful firms integrate it into as many areas as possible. Luckily for all the non-data analysts out there, this information is becoming more accessible by the day. Here are eight types of charts made possible by data visualization.
Dot Distribution Map
You’ve probably seen maps that show voter turnout over a state. Certain numbers of votes will be represented by a blue or red dot on the map. This is commonly referred to as a dot distribution map. There are many potential applications for this sort of data visualization tool. It has the benefit of being extremely easy to understand in most situations.
A scatter plot shows the distribution of data points as pertaining to two variables. These data visualization tools often will reveal patterns among data that might otherwise not have seemed particularly valuable. Connected scatter plots show a sequential progression of data when variables are fixed. However, it’s more common for the dots to be truly scattered, showing a general correlation versus a cut-and-dry line.
Temporal data visualization just shows a visual representation of how the variable of time affects other variables. There are several types of graphs and other tools that can represent this. Data visualization tools that can trend data and extract insights instantaneously are some of the most valuable for organizations trying to understand temporal trends.
It’s one of the first visual aids you learn in school. Despite its simplicity, a pie chart should be taken seriously as a valid form of data visualization. Understanding proportionality can be extremely challenging in verbal or written form. Seeing a pie chart can lend perspective to concepts that otherwise might be too abstract for the normal person.
There are several ways of formatting a tree diagram. The most important characteristic of them in general is that they branch out, similar to a tree. This kind of data visualization is extremely helpful for laying out the hierarchical nature of something.
A ring (or donut) chart sort of synthesizes the ideas of a pie chart and tree diagram into one. On one hand, it shows proportionality in a circular fashion, similar to the pie chart. It also incorporates the hierarchy of a tree diagram with the concentric layers of rings. This data visualization tool can incorporate a lot of seemingly unrelated information into one, highly relevant outline.
As the name suggests, a node-link diagram utilizes both nodes and links. What does this mean? Like a scatter plot, the nodes show certain points of data. These can be arranged in a variety of ways based on the information and intent of the diagram. The links then show how those nodes are related to one another. There can be one, or many, kinds of links that highlight the similarities or differences of various nodes.
Alluvial diagrams aren’t necessarily intuitive, but can be extremely useful for a wide range of applications. Essentially, this kind of data visualization tool shows relationships between various data streams. These diagrams flow across different time periods or other constraints, and can break into smaller flows over the progression.
These are a few of the most useful ways companies can use data visualization in order to create applicable charts. If you’re a business owner or manager, it’s a good idea to understand how these tools can potentially help you see underlying data in a new way.