Our Data Lab allows to translate raw data into meaningful insights and knowledge that support more efficient and effective healthcare decisions. Take a look at the following infographic to get a wider picture of the process.

The Data Lab guidelines are:

• Open software: Free/Libre and Open-Source Software (FLOSS) is the priority option within the Data Lab.

• Simplification of the learning curves. Especially in the “cognitive layer”, the tools must be easy to use for researchers and analysts.

• Heterogeneous data. We use the data management systems best suited to the nature of data and use cases. The Data Lab incorporates both Relational and NonSQL Databases (Not only SQL) suitable for each case.

• Data Management / Metadata Repositories. Metadata is a key tool in data governance and management processes, as it facilitates the interpretation and use of data by both individuals and automated processes.

• Centralised and distributed storage and processing. The Data Lab is easily adaptable to different scenarios, covering both a traditional analytical approach and more innovative environments where distributed storage and computing capabilities are required.