What is Data Visualization? | An Overview Of Data Visualization (2024)

It is a very challenging task to understand something that is not clear or mixed with many elements. We know the things better when intended information is clear and easy to understand. The same thing applies to data as well. We all know how data has gained popularity these days.

Organizations across the globe largely depend on the data to make more informed and data-driven decisions. Data is getting generated at an alarming rate and to process these extensive datasets, we need advanced data processing technologies like Hadoop. The process does not end with merely processing these vast amounts of data. After processing the data, it just turns out to be structured data or data which has a sequence.

To get the hidden insights or valuable information or to understand the data we need a clear explanation, and that is possible with the help of data visualization. Let’s discuss what is data visualization is all about.

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In this blog, you will be learning the following topics:

  • What is Data Visualization?
  • Need for Data Visualization?
  • How does Data Visualisation Work?
  • Types of Data Visualizations
  • Latest Data visualization trends

What is Data Visualization?

Data visualization is a process of representing data in a graphical format by using different visual elements such as charts, tables, graphs, maps, infographics, etc. There are various data visualization tools available in the market to represent the overview of the data in a user/customer understandable format. Visualization tools depict the trends, outliers, and patterns in data.

Data visualization tools are very essential for big data-related technologies. They help us in identifying and spotting the trends in data and thereby in taking data driven decisions.

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Need for Data Visualization?

Many companies across the globe are leveraging maximum benefits out of data with the help of data visualization tools. Visualization helps the organizations in analysing data analytics and in finding opportunities and threats. There are organizations like government-owned companies, hospitals, and financial institutions investing a lot in data visualization to analyse customer spending, needs, opportunities, etc.

Below mentioned are some of the causes to consider for the data visualization.

  • It constructs the way to absorb the right information
  • Visualises the relationships and data trends
  • Enables the organizations in acting on emerging trends faster than others.
  • It depicts the tastes and preferences of people belonging to specific geography.

What is Data Visualization? | An Overview Of Data Visualization (1)

What is Data Visualization? | An Overview Of Data Visualization (2)

How does Data Visualization Work?

The process of data visualization is associated with different technical aspects and involves different people like graphic designers and statisticians. There must be a proper collaboration between these people to execute the visualization process.

The below steps depicts how data is visualized.

  • Acquire data: The first thing one to do is to get the datasource from a network or a file on a disk.
  • Categorize the data:Provide some structure to the data for the understandable purpose and divide it into categories.
  • Filter:This stage involves filtering the data, which means eliminating unnecessary information from the data.
  • Mine:Use statistical models or data mining models to divide the patterns or present the data in a mathematical context.
  • Represent:In this stage, you are required to select a primary visual mode such as bar graph, list or tree, etc.
  • Refine: Add some colours and visual effects to make it more colourful and bright.
  • Interact: Add methods for controlling the data and features visible for the visualization purpose.

The following are the commonly used data visualization formats.

  • Charts
  • Tables
  • Maps
  • Infographics
  • Dashboards

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Types of Data Visualizations

Charts

A chart is defined as a graphical format used to explain the data in an easily understandable way. Human brain understands images quickly compared to text.

There are four commonly used charts, and they are,

  • Pie chart
  • Bar chart
  • Line chart
  • Histogram

Let's discuss each one in detail.

Pie chart:

The pie chart is widely used for data visualization purposes. It divides a circle into proportional segments to give a complete overview of data. Each portion of the chart contains specific information. The pie chart is often designed by considering total data equal to 100% and divides the data into specific segments. The pie chart is best suitable for data that contains a few segments. If data contains more segments, then the pie chart has to be sliced into many more sections.

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Bar chart:

A bar chart or a bar graph is also used for a pictorial representation of data. It is used to represent the categorical data with the help of rectangular bars, and each bar is proportionate to the value it holds.

One axis of the bar is used to specify the categories to compare and the other axis is used to measure the values. The below image shows how exactly a bar graph is:

Line chart:

A line chart or line graph is one of the commonly used graphs for presenting the data in a visual format. It is similar to the bar graph. In the line chart, information is displayed as small dots called ‘markers’ and are joined with the help of a line. A line chart is commonly used to spot the trends in data over a period of time.

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Histogram:

The histogram looks similar to the Bar chart, but the main difference between these two is a bar chart is used to compare two variables whereas histogram is related to only one variable. It is used mainly applied to the underlying frequency distribution of continuous data.

Tables

The table is used for comparing the categories of different products. In this process, the items which we take into consideration for comparing will be placed on column sections, and the categorical objects are placed on rows. The quantitative values are set at the intersection of the row and column, and it is called a cell.

The below-shown table would give you some sort of idea on how a tabular representation of data helps in data visualization. The below table shows the details of the payment for buying or leasing of different Cars. In the below table the first two columns are being compared about payment amounts and the other two columns contain additional information.

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Infographics

Infographic will enable you to turn the boring information into a compelling image that could be understandable by anyone. Interactive infographics play an essential role in a clear understanding of what you intend to say. Organizations across the world are using infographics as a central element to reach the targeted audience with a clear message on it.

Latest Data visualization trends.

Data has become one of the hottest topics in today's business world. Organizations have always been in search of insights out of data and to make them useful for the overall development of their organizations. The below mentioned are the five trends that had affected the data positively.

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Data beyond the visuals:

Visualization is a fundamental concept, but understanding the core concept behind the visuals is more important. Many people often stuck at the visual effects, and they are in confusion about how to incorporate those insights they have gotten out of data. Beyond the visuals, data should empower the teams to take actionable decisions.

The latest trends in data visualization are empowering team's to know even how technology works and its capabilities. The past data visualization tools are only capable of delivering its services on desktops or laptops but not on the mobile devices, and the scenario has changed due to recent developments. High capable data visualization tools are enabling the organizations to utilize the 100% of data.

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Data democratization.

It means the data democratization has been happening in each field ranging from small organizations to larger ones. Data democratization is nothing but free accessibility to data ranging from lower level employees to top authorities to take instant and accurate decisions that would positively affect the business.

Experts say that “the main intention behind developing data democracy is to remove the barriers to access or understand the data.” -Bernard Marr

In recent years the usability of data has been increased by all the departments for accomplishing their day to day tasks. Enabling data access for each department has become essential, and it helps them in taking required and valid decisions. All the department can utilize the data to optimize the opportunities and thereby to increase the profits. But the problem is all data visualizations are not yet ready to support the Data democratization.

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Storytelling with data:

Human beings are very likely to understand the data in a story format and remember for longer times. With the help of visualizations, you can create the stories that can deliver efficient, personalized and experienceable stories for its members. Embedding visualizations right into the applications and portals are helping organizations for focussing on storytelling with data.

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Data cleansing:

Data gives effective results if it is clear and contains full-fledged information. Analysing the data that contains a lot of miss information could lead to misleading of the complete information. So to tackle this problem organizations have started employing the human resources in fulfilling the data gaps. In 2019 organizations have started investing in data cleansing to eradicate the missing data problem.

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Data governance:

As the data popularity has been increasing over a period of time, there must be a secure system to protect this valuable resource. To ensure data security companies started making policies to ensure data safety, it is nothing but Data governance. Data governance contains a set of rules such as permissions, common terminology, rules for use, communication strategy, security planning, etc., are covered under this.

Conclusion

Using data visualization for presenting data would help in spotting trends and thereby improving the overall performance. Being aware of the trends could help in identifying the opportunities and to escape from the negative trends. Visualization simplifies the data and converts that into an easily understandable image format that can be remembered easily for a longer time than the text.

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What is Data Visualization? | An Overview Of Data Visualization (2024)

FAQs

What is Data Visualization? | An Overview Of Data Visualization? ›

What is data visualization? Data visualization is the representation of data through use of common graphics, such as charts, plots, infographics and even animations. These visual displays of information communicate complex data relationships and data-driven insights in a way that is easy to understand.

What is the summary of data visualization? ›

Data visualization is the process of using visual elements like charts, graphs, or maps to represent data. It translates complex, high-volume, or numerical data into a visual representation that is easier to process.

What is the meaning of data visualization? ›

Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.

What is the main purpose of data visualization? ›

Data visualization is the practice of translating information into a visual context, such as a map or graph, to make data easier for the human brain to understand and pull insights from. The main goal of data visualization is to make it easier to identify patterns, trends and outliers in large data sets.

What is big data visualization overview? ›

Big data visualization is the graphic visualization of large amounts of data. Big data itself is a huge amount of data that can be collected in real time or after a delay. However, this raw data is not especially useful by itself, but rather needs to be processed through data analytics.

What are the 4 pillars of data visualization? ›

The foundation of data visualization is built upon four pillars: distribution, relationship, comparison, and composition.

What are the 5 steps in data visualization? ›

  • Step 1 — Be clear on the question. ...
  • Step 2 — Know your data and start with basic visualizations. ...
  • Step 3 — Identify messages of the visualization, and generate the most informative.
  • Step 4 — Choose the right chart type. ...
  • Step 5 — Use color, size, scale, shapes and labels to direct attention to the key.

What is the primary goal of data visualization? ›

The goal is to communicate information clearly and efficiently to users. It is one of the steps in data analysis or data science. According to Friedman (2008) the “main goal of data visualization is to communicate information clearly and effectively through graphical means.

How to interpret data visualization? ›

Tips for reading charts, graphs & more
  1. Identify what information the chart is meant to convey. ...
  2. Identify information contained on each axis.
  3. Identify range covered by each axis.
  4. Look for patterns or trends. ...
  5. Look for averages and/or exceptions.
  6. Look for bold or highlighted data.
  7. Read the specific data.
Aug 17, 2023

What is an example of data visualization? ›

You can use bar charts to compare items between different groups, measure changes over time and identify patterns or trends. Other popular forms of data visualization include pie charts, line graphs, area charts, histograms, pivot tables, boxplots, scatter plots, radar charts and choropleth maps.

What is the conclusion of data visualization? ›

In conclusion, importance of data visualization is evident in data science, enabling businesses to draw valuable insights and make informed decisions. Both data visualization in data science are vital for a business.

What is the most important part of data visualization? ›

One thing that is of paramount importance when it comes to data visualization, it is important to generate insights through visualizations that were otherwise not obvious when looking at the dataset. Graphs and charts display information. Math has statistical concepts that help with creating and understanding them.

What is the goal of visualization? ›

Visualization is a useful technique that helps you reach your goals and live your dreams. It works by getting your mind and body ready for what you want to happen – and, just like exercise, the more you do it, the stronger it becomes.

What is data visualization in simple words? ›

Data visualization is the representation of data through use of common graphics, such as charts, plots, infographics and even animations. These visual displays of information communicate complex data relationships and data-driven insights in a way that is easy to understand.

What are the key factors of data visualization? ›

Key factors of data visualization choice include context, audience, type of data, dynamics, and the purpose of data tools. What are the common visual data analysis techniques in big data? The choice of visualization method depends on the type and source of big data and its dynamics.

What is data summarization and visualization? ›

In general, data can be summarized numerically in the form of a table known as tabular summarization or visually in the form of a graph known as data visualization.

What did you learn from data visualization? ›

Data visualization also provides a better understanding of a business's operations. Running a business requires staying on top of many moving parts, and data visualizations provide a tool that can depict multifaceted operations and how different business activities connect.

What is the mission of data Visualisation? ›

My data visualization mission statement is: Reduce the time to insight. Increase the accuracy of insights. Improve engagement.

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