Using Data Visualisation to Communicate Information


Data presentation plays the key role in interpretation of the communicated information by the audience. A variety of methods can be used to communicate information including textual forms, however, these are often overwhelming to interpret due to complexity or/and amount of data. As a result, the audience can misinterpret the information which is why it is crucial to present data in a way which is easily understood.

Human brain absorbs images a lot easier than abstract forms and for that reason many businesses, researchers and other individuals and organizations which deal with collection, analysis and presentation of data use data visualisation. It refers to the use of visualisations such as maps, dials, graphs, charts, etc. to communicate information in order to enable the audience to absorb and interpret data quickly and easily. Using data visualisation itself, however, does not automatically guarantee an efficient and accurate interpretation of the communicated information by the audience.

Data collection and analysis are the very most important factors in communication of information. Before you start choosing which data visualisation methods you will use to communicate information, you need to know exactly what you want to communicate. Then, you need to decide which method you will use to present data – deductive (starting with the results of your analysis and then explain how you came to the conclusion) or inductive (communicating the conclusion in the end of the presentation). Which one to choose depends on the type of information and type of data you want to share.

Aesthetic appeal is another advantage of data visualisation over the traditional modes of data presentation because the visualisations look more appealing than the textual forms. However, it is important to keep in mind that the main goal of data visualisation is to communicate information in a clear and understandable way. When communicating information by the use of data visualisation, you should therefore make sure that it is both functional and good looking. If you are dealing with a large amount of data, consider creating multiple visualisations rather than trying to show everything in one mega visualisation.

In the end, it is important to choose the right data visualisation tools. Nowadays, most of the work is made by the computers in no time, of course, under condition that you have the right data visualisation software. A number of software programmes exist which are designed to meet specific needs of their users. Many are open source and are freely available but a great deal of them are proprietary. However, they are not necessarily better than those that are free. In order to make the best choice possible, focus on data visualisation software programmes which tend to meet your needs the most and try them out before making the final decision. Most companies that offer proprietary programmes also offer a free trial period which gives you enough time to determine whether their software is what you are looking for to communicate information in an effective and visually appealing way.