Data Visualisation Techniques

1. Visualizing the Data: Create Clear Stories Using Data Visualization

Data is a big part of our everyday lives today. Whether we’re looking at a business report, a student’s performance review, social media analytics or the amount of traffic that visits a website every second, we can see that there is a lot of data produced on a second-to-second basis. The problem is that data in raw format (tables and numbers) is very hard to interpret by most people. Data Visualisation has made this very simple for everyone. Data Visualisation allows you to turn complex Data into easy-to-read Charts, Graphs and Dashboards. You can quickly gain insight into what is going on in your business.

As such, learning Data Visualisation will be crucial for Beginners and entry-level IT Professionals. Data Visualisation is the bridge between the data that you are analysing and the decisions that you will make based on that data. When Data is presented as Visual, it is much easier to Analyse, to communicate and to act on. This​‍​‌‍​‍‌​‍​‌‍​‍‌ article will explain different data visualisation techniques in a way that is accessible and simple to understand for anyone. Hence,​‍​‌‍​‍‌​‍​‌‍​‍‌ the audience will understand how a data visualisation tool works, and they will also know the story that is coming from the visuals.

2. What Is Data Visualisation?

Data​‍​‌‍​‍‌​‍​‌‍​‍‌ visualisation is a way of showing data using visuals like charts, graphs, or any other form of visual. By looking at the data, users can find trends, differences, and exceptions without the need to go through long data tables. Therefore, this method of presenting is a means of facilitating the reading, interpretation, and understanding of ​‍​‌‍​‍‌​‍​‌‍​‍‌data.

Both technical and non-technical users can clearly view the same data and make better decisions based on the data visualisations.

3. Why Data Visualisation Is Important

Most industries utilise data visualisation heavily. Companies use data visualisation to evaluate how well their operations are performing; educators use this method to explain difficult-to-understand concepts; and government agencies use visualisation as a means of communicating public information in a manner that reduces confusion and enhances understanding.

Visually interpreting information is a natural way for humans to do. Visual data is interpreted by humans up to four times quicker than text or numerical data. Therefore, a user can easily comprehend a well-designed chart in a matter of seconds, while a user could spend several minutes attempting to decode what the same information would mean by just examining a table of numbers in a spreadsheet. In addition, data visualisation encourages people unfamiliar with data interpretation and presentation to become more confident about effectively presenting the information and interpreting it.

4. Common Visualisation Approaches

Many different methods exist to provide various ways to interact with and understand data.

★Charts and Bar Charts

Bar and Column Charts are two of the most popular visualisation techniques; they are used to display comparisons across different types of data (categories). For example, 

✔Bar Charts 

✔Column charts

✔Comparisons on vertical lines

make it easy to compare sales for various months or for different teams, while Column Charts would display these comparisons on vertical lines. Bar Charts are easy to read and are a good starting point for individuals who are new to data visualisation because they provide a clear understanding of how values compare to one another.

★Line Charts

A Line Chart is an excellent choice to represent the trend of data over time, and it allows the presenter to show any changes, increase or decrease in a particular area of interest, by connecting the 'dots' of data over time (i.e., eBay sales for 10 years). This makes it easy to track progress and find any growth patterns in the line chart (whether quarterly or yearly). Line Charts are used extensively in business analytics and to monitor the performance of businesses.

Looking at the relationships in pie charts, there are several potential types of relationships we can see, depending on how the sections of the pie chart are represented.

★Area Charts

Area charts provide a visual representation where the area under the line represents the cumulative total over time. The cumulative volume and trends of the data become visually apparent. Area charts tend to have a good visual impact.

Although similar to a line chart, an area chart has its place in financial and resource dashboards, like when we want to track the cumulative total of resources we have received.

★Selecting the Most Appropriate Visualisation Approach

The choice of visualisation approach depends on the nature of the data and the message. The intended audience is also a major consideration in determining the appropriate type of data visualisation. A technical audience would probably desire more detail in their charts

5. Data Visualisation: Principles of Effective Practice

There are established principles for producing effective data visualisation. For example, the design should be kept as simple as possible and free of clutter in order to communicate the intended message effectively. Using clear labels, using readable fonts, and selecting colours that are suitable for use in a data visualisation will all assist with the interpretation of the data visualisation.

6. Tools Available to Create Data Visualisations

A range of tools is available for the purpose of creating data visualisations. New users will generally begin using 

➜Spreadsheet applications (e.g., Excel) 

➜Simple data visualisation (e.g., bar charts)

As users become more familiar with the data and develop their data knowledge, they may find other specialised data visualisation solutions to create dashboards, interactive data visualisation, and so forth.

7. Data Visualisation – A Key Career Skill

All types of data visualisation (both internal and external) are important across many 

✅IT (Information Technology) jobs

✅Non-IT jobs

✅Most data analysts

✅Business analysts

✅Marketers, and 

✅Product managers

 are likely to spend a significant amount of time developing data visualisations. Even developers and designers spend time developing data visualisations to present their insights into the business, and they use these insights to communicate their findings.

For new graduates/working professionals, mastering data visualisation is an additional way of increasing employability as it demonstrates the individual has an analytical thought process, communication capabilities, and the capability to work with data effectively and efficiently.

Data Visualisation in the Future

The increasing amounts of data being generated will require professionals able to produce simplified, visual representations of that data. Data visualisation skills are essential to prepare today's beginners for future job opportunities.

Conclusion

Data​‍​‌‍​‍‌​‍​‌‍​‍‌ visualisation techniques are a great aid in that they enable you to take a large amount of data and create a picture, which is known as a visualisation of the data. With data visualisation techniques, you can handle huge volumes of complicated data and still grasp what it is in a very short time. It follows that you can decide when you have data visualisation techniques at your disposal. Data visualisation techniques are good tools that help you in your data ​‍​‌‍​‍‌​‍​‌‍​‍‌work.

In​‍​‌‍​‍‌​‍​‌‍​‍‌ case you are beginning, soothe yourself. Utilise the essential graphs. Experiment, figure out what works for your work, and learn a couple of moves to keep your work neat. There is a heap of help on the internet, thus it is very simple to plunge into. Keep it up for some time, and by that time, you will be able to find patterns in your data which you could not have seen ​‍​‌‍​‍‌​‍​‌‍​‍‌before.