Real Consumer Data for Predictive Models
Our vision is a world where everyone can make better decision based on real data and expert models.
Data modelling and data science rely on quality data in order to produce robust and valid results.
For example, as part of an EU FP7 project consortium (Food4me), we are gathering food intake and nutritional profile information in order to provide personalised nutrition advice directly back to consumers. This is carried out through a user-friendly web interface using a Food Frequency Questionnaire (FFQ).
Secure Industry Data Transfer
We work with industry to gather and anonymise data in order to create predictive models.
We provide standard data templates and a secure data upload service on our site to facilitate convenient, secure and accurate transfer of data from partners to us.
Data Validation and Checking
When we have received the data, we analyse data and carry out standard checks as part of our quality assurance process.
We use statistical tools to visualise the data in order to understand important factors in our models.
Predictive Models Delivered
The data is combined with our predictive models in the cloud to provide simple and powerful access to decision making tools for our clients.