Data Visualization
Over 2.5 quintillion bytes of data are produced every single day, with 90% of all data produced in the last two years, according to DOMO. Making sense of this enormous volume of data is a challenging undertaking.
The graphic display of information and data is known as data visualisation. Data visualisation tools offer an easy approach to observing and analysing trends, outliers, and patterns in data by utilising visual elements like charts, graphs, and maps.
What Is Data Visualization?
The act of turning raw data into graphical or pictorial representations, such as charts, graphs, diagrams, photographs, and films, that explain the data and enable you to learn from it is known as data visualisation. Therefore, users can efficiently produce reports and swiftly examine the data to make business decisions.
Why Is Data Visualisation So Crucial?
Using visual data, data visualisation offers a rapid and efficient approach to conveying information to all audiences. Additionally, the practice can assist businesses in determining the variables that influence consumer behaviour, identifying areas that require improvement or additional attention, making data more memorable for stakeholders, figuring out the best times and locations to sell particular products, and forecasting sales volumes.
The Different Types Of Visualizations
Probably the first thing that comes to mind when you think of data visualisation is a straightforward bar graph or pie chart. Although they might be a crucial component of data visualisation and a standard starting point for many data graphics, the proper visualisation needs to be combined with the right set of data. Simple graphs are just the beginning. There are many different visualisation techniques available to present data in attractive and useful ways. Typical kinds of data visualisation in general:
- Charts
- Tables
- Graphs
- Maps
- Infographics
- Dashboards
Data Visualisation Examples
The most popular visualisation method, in the beginning, was turning data into a table, bar graph, or pie chart using a Microsoft Excel spreadsheet. Although traditional visualisation approaches are still frequently employed, more sophisticated ones are now also available, such as the following:
- bubble clouds
- bullet graphs
- heat maps
- fever charts
- time-series charts
Conclusion
Numerous technologies are available for data processing and visualisation. These range from easy to difficult, clear to obscure. Not every tool can scale to commercial or business objectives, and not every tool is appropriate for everyone wishing to master visualisation techniques.
Feel free to study up on the possibilities here or delve into in-depth third-party research like the Gartner Magic Quadrant if you want to learn more. Additionally, keep in mind that sound data visualisation philosophy and techniques transcend particular technologies and products. Focus on recommended practises while mastering this skill, and when it comes to dashboards and visualisations, experiment with your unique personal style. Since data visualisation won't be going away anytime soon, it's crucial to lay a solid analytical foundation.
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