Do you have a database that you haven’t been able to analyze? As you understand, by analyzing the data we have, we can maximize our business potential. With the increasing need for data processing professionals such as data scientists and data analysts, you don’t need to be a professional to be able to process data properly.
Learning basic data visualization techniques can help you extract information without having to be a data science or data analyst professional. The benefits you can get are more confidence in policy execution and the potential to increase your company’s revenue.
Several data visualization techniques can help you improve your ability to read data. Professionals commonly use the following techniques to visualize data.
What is data visualization?
Data visualization is a process of converting raw data into a graphical display, which can be in the form of diagrams, graphs, histograms, or word clouds, with the aim of showing trends, highlighting small details, and effectively communicating complex datasets.
Many data visualization techniques exist, but today I will discuss several commonly used examples in data visualization.
Data visualization techniques
Different types of diagrams can visualize data depending on the case. The following are some commonly used graphs.
- Bar Chart
- Pie Chart
- Histogram
- Heat Map
- Scatter Plot
- Word Cloud
- Correlation Matrices
- Network Diagram
- Choropleth Maps
- Timeline
1. Bar Chart
Bar charts are one of the most commonly used visualization techniques. The graph’s axis represents the categories being compared, while the length of each bar shows the value of those categories.
One weakness of bar charts is that including too many categories and values can make the visualization unclear. Bar charts are suitable for people who are not too concerned with the details of the information and only want to know the outline of the information.
2. Pie Chart
Pie charts are also one of the most commonly used data visualization techniques. This visualization can be used for various purposes. Pie charts are used to show the proportions between categories or parts of one category and another.
Like bar charts, pie charts also do not work well if too many categories are included. Pie charts are not suitable for displaying overly complex data.
3. Histogram
Unlike bar charts, histograms divide data into specific intervals or periods of time. This visualization is useful for determining where data is concentrated in a given period and the size of the gap between periods.
Histograms are very useful for viewing data trends over time. For example, if you own a supermarket and want to know which days are the busiest, you can easily find this information using a histogram.
4. Heat Map
A heat map is a data visualization technique that shows differences in variables through different colors. This type of visualization is very easy for readers to understand in order to grasp trends in the data. In addition, legends also play an important role in making heat map visualizations easy to read.
One application of heat maps is to use them to visualize beverage sales at a cafe, with white indicating high sales and black indicating low sales.
5. Scatter Plot
The next technique for data visualization is the scatter plot. A scatter plot visualizes two variables using vertical and horizontal axes, with data represented by dots. This visualization technique is useful for showing the relationship between two variables. Scatter plots are usually used to determine trends or relationships between data.
Scatter plots are suitable for large datasets. This is because it is easier to see a trend when there is a lot of data. In addition, the closer the data points are to each other, the stronger the relationship between them.
6. Word Cloud
A word cloud or tag cloud is a visualization technique that shows how often words appear in a dataset. The more a word appears in a dataset, the larger it will be in the visualization.
Word clouds are commonly used by companies to gain insight into customer perceptions of the products they sell. For example, a company might collect data from Google reviews and find that the words most frequently used by customers are “high quality,” “long-lasting,” and “ cheap.” Based on this data, the company can improve its services.
7. Correlation Matrix
A correlation matrix is a table that shows the relationship between two variables, and the colors used indicate how influential the relationship between the variables is.
In business, correlation matrices help identify the relationship between two variables, such as advertising and sales. This technique allows finding the most effective pattern—for example, advertising three times a week may yield better results than advertising more than three times a week.
8. Network Diagram
A network diagram is a visualization technique that shows the relationship between qualitative data. A network diagram consists of two main components, namely nodes and links, also known as edges. Nodes are data connected to other data using edges. The purpose of this visualization is to show the relationship between nodes.
The application of network diagrams is very diverse. For example, in a company, they can be used to show the relationships between employees inside the company.
9. Choropleth Maps
The next visualization technique is choropleth maps. Choropleth maps use colors, shading, and other patterns to show specific patterns on existing maps. This visualization technique uses colors ranging from light to dark to show data density.
Choropleth maps allow readers to see differences in variables between regions. The disadvantage of this visualization technique is that we cannot see the exact numbers for each color, because the colors used only indicate a range of values. However, you can also add descriptions for each region.
10. Timeline
The last visualization technique is the timeline. The function of the timeline visualization technique is to present information, events, or processes in chronological order. It usually uses a linear scale to show the development of a process over time.
Timelines allow you to highlight patterns that exist within a specific time period. Although timeline visualization techniques are simple, you can enhance them using various colors and add photos if necessary.
Also read: Learning how to learn