Data science and machine learning in engineering
Applications in Engineering
Data science is revolutionizing the engineering sector. It provides new methods for monitoring, operating, optimizing and maintaining technological assets.
Why VORtech Data Science?
What makes VORtech special as a data science company? How will VORtech cooperate with you to reach the best result? You will find the answers here.
Data Science Projects
These projects illustrate what data science can do for utility companies and engineering companies. VORtech helps to unlock the potential of new methods in the technological sector.
Finding and locating Leakages
Leakages in distribution networks can be found by using a combination of sensor readings and a computational model.
Avoiding unsuccessful Home Visits
VORtech analyzed a data set about service men calling on customers who ware not at home. The number of such unsuccessful home visits can be reduced significantly by exploiting patterns in the probability that people in a certain area are at home.
Insights for Water Boards
Water managers in the Netherlands are responsible for an extremely complex water system, where the impact of actions is not always obvious. Therefore water managers need more insight into the relations between variables in their system.
Our data science services
Data scientists on a flexible basis
Through our specific secondment scheme, we offer our clients a special combination of flexibility, continuity and quality.
Developing data science applications
The amount of data that is generated in the technological and scientific sectors is growing by day. Building applications to analyse this data and turn it into reliable and useful information is VORtechs core competence.
Data Science Consultancy
Many companies are still searching for the right way to leverage data science. VORtech can help you explore the possibilities and to set up projects.
Big Data MBA
What if you are, say, an engineering company with loads of experience in building complex installations but without any data science background. Where do you start?
Why bother with computational models if you’ve got data?
Are we indeed witnessing the end of traditional mathematical modelling and should its practitioners be looking for a new job?