Data visualization refers to the intuitive presentation of data features using graphics. Its graphical nature can help decision makers grasp complex concepts and discover new data patterns, and thus has become an essential part of big data analysis. It aims to enable students to (1) understand the characteristics of data, (2) master the use of the three major graphing systems of R language, and (3) be able to produce the analysis process into a report and publish it for communication.

Employment Prospects:

In the data analysis work, data visualization is only the last step, but it is also an essential step, as if a product is no longer outstanding, but also has to have a platform to show itself, in order to allow the audience to see its excellence and charm.

The first trend in data visualization efforts is collaboration, due to the fact that data warehouses are a centralized source of data, but the real analysis and insights happen on the desktop, manually combining multiple sources. Next-generation platforms allow multiple users to publish data sources, algorithms, and insights through APIs or data virtualization. Such a requirement if realized can increase efficiency for our work.

It is increasingly applying machine learning and artificial intelligence to process structured and unstructured data sources. Cutting-edge organizations are applying these tools to previously inaccessible data.

Small Si recommended schools for students below; Oxford, Cambridge, Imperial College London, Durham, St Andrews, University College London, Warwick, Bristol, Manchester, The first time I saw this, I was in the middle of it.