What is Data Visualization, Its Functions, Types, and Tools

Data visualization is a graphical representation of information and data. With visualization, complex data can be presented in a simpler form that is easy for many people to understand.

What is Data Visualization

Data visualization is a graphic or visual representation of information and data. This means that the visualization of a dataset appears simpler and is easier for many people to understand. Each visual element makes it easier to identify patterns in data, understand trends, and spot outliers. Data visualization serves to help people understand the significance of data by placing it in a visual context.

Especially for businesses, visual data can clearly display analytics from multiple datasets at once. This makes it easier for decision-makers to create new strategies for business improvement. In fact, people who struggle to interpret analyses through text or raw data can quickly understand the insights through visual displays, which are simple and easy to interpret.

Functions of Data Visualization

Data visualization is important because it serves several functions:

1. Easy Communication
   The main function of data visualization is to facilitate communication between stakeholders or anyone in a business role. Small or large businesses store a lot of data for various purposes. Data includes daily, weekly, monthly, and even yearly figures, which change frequently. Through visualization, data is easier to understand by anyone viewing it, displayed in a clear and attractive format. Business outcomes are presented based on relevant variables.

   With data visualization, business leaders can make decisions and plan advanced strategies for business development. Raw data, in contrast, may appear complicated and confusing, especially for non-experts.

2. Faster Decision Making
   Data presented visually enables business professionals to easily grasp the essence of business development. The data can be closely analyzed, strategies can be devised, and decisions can be made quickly. Without visualization, incomplete or unstructured data would take a long time to understand, leading to delayed decision-making.

3. Easier Idea Expression
   Visualized data that is easy to understand sparks new ideas from business teams. As a result, team members can more easily express and combine their ideas to reach decisions. In contrast, raw data requires more time to interpret, and expressing ideas becomes more challenging and time-consuming.

4. Problem Identification
   Problem identification is another key function of data visualization. By analyzing the elements of each variable, data becomes valuable information that provides insights into trends and patterns. Identifying existing problems can lead to discussions about how to address them, reducing potential losses. Visualization offers new insights into how critical visuals are for understanding business developments in detail.

5 Types of Data Visualization

There are several types of data visualizations, with five common ones:

1. Temporal
   Temporal visuals display results in a linear or one-dimensional format. This type is characterized by lines that begin and end at specific points, and these lines can stand alone or intersect with others to form a complete data display. Common temporal visualizations include scatter plots, time series, timelines, and line graphs.

2. Hierarchy
   Hierarchical visuals are useful for showing relationships between groups, particularly for illustrating the hierarchy of one group within a larger one. This type is often used for business explanations or educational purposes, such as tree diagrams.

3. Network
   Network visuals highlight how elements influence each other. With directional visual cues, network visuals make it easier to explain relationships between data points. Common examples include word clouds and Instagram node-links.

4. Multidimensional
   Multidimensional visuals are ideal for datasets with many variables. These visuals help simplify complex data by presenting it in an easy-to-understand format. Examples of multidimensional visuals include pie charts, stacked bar charts, and histograms.

5. Geospatial
   Geospatial visuals offer a comprehensive overview of data by representing the real-world locations or spaces of objects. These visuals are often used for regional sales, business growth maps, and flow charts. They look like maps, with specific colors that represent data. Examples include cartographs and heatmaps.

Each visual type can be chosen based on your needs to ensure that the display aligns with the elements or variables being presented, making it easier for anyone to understand.

Examples of Data Visualization Tools

To create visually attractive and easy-to-understand visuals, various software tools are available. These tools allow users to input data and variables, transforming them into engaging visuals. Examples of Data Visualization Tools inclue

1. Microsoft Excel
   A familiar Data Visualization Tool, Excel is accessible for beginners and is useful for quickly processing and visualizing data. Its simple interface makes it a popular choice for summarizing data visually.

2. Tableau
   Tableau is powerful for creating compelling charts, maps, and graphs. It offers a complete set of features, including collaboration tools for team members.

3. QlikView
   QlikView helps integrate multiple databases and spreadsheets, making it easier to convert data into visual formats like bar charts and pie charts. It’s user-friendly and time-efficient.

4. Microsoft Power BI
   Ideal for detailed reporting and analysis, Power BI centralizes visual data for easy access by all team members.

5. Google Data Studio
   Google Data Studio is a free Data Visualization Tools, that integrates with Google Analytics, Google Ads, BigQuery, and spreadsheets. It helps create visually attractive graphs, tables, and charts.

6. Sisense
   Sisense is a robust option for creating data dashboards, offering advanced AI technology for more detailed analysis.

Data Visualization Tools simplifies the process of creating clear, attractive, and informative visual representations, allowing users to present data efficiently and effectively.

Conclusion

Data visualization is essential for helping people understand complex data quickly. By choosing the right visual type and utilizing the proper tools, businesses can present their data in an easily digestible form, speeding up decision-making and improving communication.

Reference

Fernando, D. (2018, November). Data visualization using Google Data Studio. In  Proceedings of the National Seminar on Information Technology Engineering | SNARTITION  (Vol. 1).

Author: Meilina Eka Ayuningtyas