uptodate wants to use data science to enhance the customer experience and offer new services. To achieve this, they need to identify which ideas showed most promise and then verify and implement these ideas. At the same time they also need to build the required infrastructure – from dashboards and data storage to machine learning models. A key point from the outset is ensuring regulatory compliance in handling customer data.

New, cloud-based data infrastructure 

Zühlke assembles a project team and uses its international pool of data scientists, machine learning experts and data engineers to ensure maximum flexibility in adapting the team to any new challenges. Working with experts from uptodate, the team identifies promising use cases, validates the business case for these use cases and uses agile methods to support their implementation. In an iterative process, this produces a cloud-based data infrastructure based on concrete applications. 

The joint team also developes measures to ensure GDPR compliance, such as automated, full deletion of data records on request.

Startup becomes a Data Driven Company 

The new infrastructure enables uptodate to apply and scale machine learning models. Machine learning models for churn prediction, image processing, recommender systems, etc., generate genuine added value for uptodate and provide invaluable insights. Specially tailored dashboards enable the start-up to ensure that all decisions are based on data – uptodate has become a data-driven organisation.

The newly developed processes ensure that all GDPR requirements are met and enable effortless, lightweight integration of new data and applications.