Projects

Each data application has a different objective or purpose. But most applications are made up of a combination of the following functions.

• Data: All applications are data driven and data forms the center of each app. In some cases data are already available and have to be combined into a single repository to be queried and reported on. In other cases no data is available and the application allows users to capture data or receive data from outside sources. In all cases the data has to be managed and monitored with automated tasks to report the status of the data source to the front end users.

• Analytics: In most cases the core functionality is to analyse the data to find insights from it. Techniques ranging from graphical analysis to machine learning are used to identify hidden patterns and trends and to predict future values.

• Visualisation: Once analysis is done the next key step is to present the results to the reader in a way that will allow them to act upon the results.

• Processes: And in some cases these actions can become automated tasks. The applications can manage these automated tasks by starting and stopping them while reporting to the front end user what is happening. Detailed analysis of these processes identifies successful actions and areas that can be improved.