Converting health data into a common data model, creates a precondition for systematic analysis of data coming from different sources and enables using various tools developed for this particular model.

Turning health data into valuable knowledge requires right methods for compiling and interpreting data. Data visualization enables to rely on a large amount of data in a compact space. Instead of spending hours on going through endless rows of data, visualization solutions will interpret the data quickly and efficiently.

Various text analytics tools enable to turn text into quantitative data, that is, to change it into a format suitable for calculations. This way, text documents can be quickly searched and analyzed, furthermore, text analytics enables to automatically anonymize sensitive health data.