STACC has successfully implemented its data science and machine learning competence in public sector to process data volumes and develop new solutions. Contact us if you’d like to benefit from our experience.
The convenience of using e-services offered by the state can be greatly improved with the help of recommendation system, by recommending suitable services (e.g. actions related to childbirth) or products (e.g. job offers or social security benefits) tailored to the profile of a specific user.
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 pseudonymize data for publishing open data.
Machine learning enables to use the data generated in public sector to learn how to improve the efficiency of activities and how to deliver the best quality services to society. As a result of the analysis, it becomes clear how much value the data has and how exactly can machine learning be implemented on that data.
Process mining enables to collect and analyze the massive amount of big data in public sector to gain insight into existing business processes, identify problems such as bottlenecks, and find ways to improve overall operational workflow.
A tool for pseudonymizing the database about gas and electricity consumption, which was a prerequisite for creating an open database
MINISTRY OF ECONOMIC AFFAIRS AND COMMUNICATIONS
Service catalog analysis for connecting public services and life events