Data valorization is at the core of any data related projects.

This stage consists in identifying amongst all the collected material the specific data that has the potential to create value and in determining how this can be achieved. The very first step is to determine what is the value: it can be linked to the economical benefits, of course, but it is also possible to define the value as an increase in quality, substance or consistency of the existing data. The objectives linked to a data valorization project are diverse and depend on the application fields.

In the field of human resources, data valorization can highlight certain causes for absenteeism, following precise criterias: department, age, position, seniority, working hours. In an entirely different field, such as customer behavior analysis, data valorization can also improve the CRM knowledge base in order to facilitate and accelerate decision making. Finally, in the field of quality control in the production of specific items, this process allows the business to minimize losses by maximizing input information.

Data valorization is also valuable at the beginning of a predictive analysis project: an in depth study of the data allows us to determine different use cases.

Industry 4.0 is an appropriate candidate: the sensors collect enormous amounts of raw information on which numerous Big Data projects are worth considering: breakdown and failure detection, anomaly detection, engine health status.

Data valorization is based on high level mathematical concepts, therefore the stages of data study, cleaning and exploration require specialized in depth knowledge. The technical stage of feature engineering is used to bring hidden and untapped information to light. Finally, the visualisation stage offer a user-friendly and interactive way to understand the data. In other words, data valorization is the new way of approaching Business Intelligence (BI).

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Use Cases

Human Resources

Often regarded as inapplicable to data science, human resources have been falsely pushed aside. Predicting an employee’s leaving, anticipating burnouts or addressing gender equality concerns are all issues to which our team can offer solutions.

Customer Behavior

Predictive scoring, automated identification or segmentation models are the main issues in marketing. Swiss-SDI offers an in-depth analysis of your CRM data which allows you to better understand customer behavior in order to optimize your decision making processes.

Quality Control

Quality control is an essential issue for production chains. Artificial intelligence methods now make this step possible with no waste. Swiss-SDI prepares tailor-made control solutions built on the data collected by your sensors.