Visualization plays a crucial role in representing data in our daily life. Individuals, businesses, and the government rely on visual tools to understand data in their geographic regions. Thus, these entities can reference and implement the information they get to meet their objectives.
Of course, it can be challenging to implement datasets, especially over a large geographic area. Hence, there is a need to utilize cluster maps, a visual tool that provides clear and straightforward solutions for users.
This guide dives into cluster maps, including some pivotal examples and applications. It also discusses how you can create and use them effectively for your business or personal use.
What Is a Cluster Map?
When organizing large datasets regarding geographic regions for your business, there is usually a challenge to present your data in the most transparent way. The simple solution is for your data to be in “clusters” or “groups.” Data clusters support various socio-economic development so businesses can channel their resources into the most vital areas.
When data exists in clusters, getting the appropriate information and implementing it becomes easy. Then, you may wonder, “what is a cluster map?” The answer can help you figure out how to use it in displaying data.
A cluster map is a visualization tool that displays data points of a geographic location on a map. The aim of using one is to display the distribution of data across a geographical area. You can use pins or colors to represent different data points in certain regions.
Furthermore, through its color scheme, this type of map shows areas with denser data points and those without. Thus, you can use the given information to predict a pattern or trend in data. Cluster maps combine data from nearby sources to create a single data point. However, the data you want to analyze and the clustering algorithm may provide varied results to users. Still, you can get the desired data cluster to utilize in future operations.
Cluster Map Examples
Now that you understand this type of map, let’s consider a cluster map example that potentially saved billions of lives. Remember the COVID-19 pandemic? The global pandemic led to data collection on people affected by the virus across continents and countries. Upon receiving figures in the form of data, the government identified regions with larger data points. Then, they provided stricter measures to ensure everyone’s safety.
The government gave more attention to regions with larger clusters (like Asia and Europe) regarding healthcare, sensitization, lockdowns, and more. Also, areas that had lower figures or had smaller clusters had their preventive measures. This is one key example of how cluster maps were instrumental in handling the global coronavirus pandemic.
Apart from the COVID-19 pandemic, cluster map examples are common in the following sectors:
- Marketing
Companies and businesses use cluster map forms to identify areas with high customer concentration. This visual tool will help them to streamline their marketing strategy towards this area, thus expanding their business.
- Infrastructure Planning
Government can utilize them to identify areas with high concentrations of infrastructure like hospitals, buildings, apartments, parks, etc. This information can help urban planners identify and build new facilities in areas with less.
- Security
Security and law enforcement officials can utilize these maps to identify areas with higher crime rates. It becomes effective as these officials can identify trends in criminal activities and employ available resources.
Cluster Mapping Tool
To successfully create cluster maps, you need a cluster mapping tool. This tool helps you perform necessary cluster analysis to identify locations with more or fewer data points. It can help provide essential information to users and implement needed actions.
Since it is not a one size fits all tool, you need to define your parameters so it can serve your needs transparently. Various software tools include GIS (Geographic Information System) software, statistical analysis software, and specialized data visualization tools.
5 Steps To Create Cluster Maps
Map makers like ArcGIS Pro, Maply, and Mapize have customized cluster mapping tools embedded in their platforms, which create cluster maps accurately and excellently. If you want to create a cluster map, here are the five steps to follow.
Step 1: Determination of Data
The first step in creating them is to determine the data you want to analyze on the cluster map. You can collect and format data from several sources and include the necessary parameters and variables for your analysis.
Step 2: Select a Cluster Mapping Tool
The next step is to select your choice mapping tool to create your cluster maps successfully. While various popular tools exist, they have their strengths and drawbacks. Several mapping software can put you on the right track in creating these maps. They contain a wide range of customization options for your mapping needs.
Step 3: Import Your Cluster Map Data Into the Mapping Tool
After selecting your mapping tool, you must import your data in the correct format. Your data can be in the form of a spreadsheet or CSV file. You can also import your data via an online database. It would help to utilize the proper format for your mapping tool to avoid hiccups when creating the cluster maps.
Step 4: Map Settings Configuration
After successfully importing your data, the next step is to configure your map settings. This includes selecting color schemes, grid size, geographic parameters (longitude and latitude), and other necessary parameters.
Step 5: Run the Clustering Algorithm
After inputting the necessary parameters, run the clustering algorithm. This process involves grouping a single piece of data into clusters. Afterward, you will have results in clusters on the map, showing areas with clustered data represented by a color scheme for easy reference.
Closing Thoughts on Cluster Maps
Cluster maps are excellent visualization tools that help represent large datasets. They combine data points into clusters or groups according to their proximity. They have many practical examples and applications, including public health, marketing, and crime analysis.
If you want assistance in data clustering and spatial data, Mapize is your go-to mapping platform. One peculiar feature of Mapize is its user-friendly interface, which makes it easy for users of all skill levels to work with spatial data.
Also, the platform’s drag-and-drop functionality allows users to quickly and easily create custom maps and visualizations. At the same time, its intuitive data analysis tools make gaining insights from spatial data accessible. There are other customization options with Mapize without needing any coding experience. Try Mapize today and create your first map.
