Data visualization is important in the field of business that aims to support decision-making in a timely and accurate manner. This is because data visualization invites us to understand something visually and interestingly. So it will also be much easier to understand something.
Because many people find it difficult to comprehend an analysis result in writing by simply reading it out loud. Why can this happen? This happens because our brain reacts much faster to visual data such as pictures, graphs, charts, etc.
So what exactly is a clear understanding of this data visualization? Why is data visualization so important? Don’t worry, you are in the right article! We will help you fully explain data visualization using the following information!
Definition of Data Visualization
Data visualization is a set of processes for displaying data or information in a form that is not difficult to understand, such as images, graphs, numbers, charts, and so on. Data visualization can simplify the collection of all data to be displayed.
The use of visual elements in this method makes it much easier for readers to identify and understand patterns, outliers, and trends in data. This method will also enable decision-makers to make the right decisions by viewing data analysis in visual form.
However, the application of using data visualization must also be accompanied by a clear understanding of why it is so important, what types exist, and what tools are used.
Why Is Data Visualization So Important?
The answer to the question of why data visualization is so important is that it will be very difficult for us to search and collect large amounts of information at the same time. This is even more true if the information is still in raw or written form.
Therefore, we need data that is presented visually to facilitate understanding of the data in a short time. Understanding the data obtained does not take much time and is naturally accurate, making it easier for the reader to make decisions.
5 Types of Data Visualization
There are several types of data visualization that you can use. Of course, each type has its meaning and role in conveying an analysis. Want to learn more about the types of data visualization? Take a look at the explanation below.
1. Visualization of Temporal Type Data
One type of data visualization that is commonly used in a company or business person is the temporal type. Usually, this type of temporal data visualization is used to display the results of a set of data that is linear or only one-dimensional.
The characteristic of temporal data visualization is that it is a line that starts and ends at a certain point. Examples of this type include scatter plots, timeline plots, and time series plots.
2. Hierarchical Data Visualization
The next type of data visualization is the hierarchical type. This type is used to show the relationship between one group to another larger group. In addition, this type of hierarchy is also useful for displaying new data that originates from a cause. An example of using hierarchical data visualization is a tree diagram.
3. Network Type Data Visualization
Data sets or datasets are fundamentally interconnected within an organization and can influence each other. Therefore, the function of this network-type data visualization is to facilitate the relationships that exist between each of these data sets. Examples of this data visualization include word clouds and node-link diagrams.
4. Visualization of Multidimensional Type Data
As the name suggests, this type of multidimensional data visualization is suitable for visualizing data that has many variables or dimensions. Given the large number of data sets displayed, this type of visualization is usually made more attractive and eye-catching to make it easier to understand. Examples of this type of data visualization include pie charts, histograms, and stacked bars.
5. Visualization of Geodata
The last type of data visualization is geospatial data. This type can represent the real form of an object or space that has data to display. In general, geospatial information is commonly used to display sales penetration in an area, business growth maps, and flow at a point. Examples of geospatial data visualization include heat maps and cartographies.
The 4 Best Tools for Data Visualization
Of course, for you to realize the function of data visualization, it must be balanced in practice with the use of the best tools. What data visualization tools can be used? We have it covered for you. So, see below for more.
Tableau is a tool that is quite popular for use by data analysts because the built-in graphical analysis that this tool has is quite interesting. The ability of tableau tools is to be able to process data using a combination of visualization and data analysis.
Using these tools, you can create simple graphs to creative and interactive visualizations. The advantage of this tableau lies in one of its features which does not require you to write code or syntax to use this data visualization tool.
If you want to create complex charts and graphs, this one tool can do the trick for you. Another advantage of D3.js is that you can use it across platforms. This is because this tool is open source and allows you to use it across different operating systems such as Android, iOS, and Windows.
4. Data Wrapper
The next data visualization tool you can use is Data wrapper. Using these tools helps in creating any type of chart. Not only that, but Data wrapper is also capable of creating modifiable maps and responsive tables.
The user interface of this tool is pretty straightforward and clear, making it pretty easy to use. It is also capable of creating visual data that can be quickly attached to reports.
This is an article that explains the importance and use of data visualization and its types that you can use. To what extent are you interested in using the data visualization method when you want to convey an analysis result? Of course, I hope the above information can help you.