Applying Data Science: the question is key
Data Science can be extremely successful in practice if the right models and algorithms are used to answer an important business question, if existing domain knowledge is used and if Data Scientists work closely with all other relevant stakeholders.
This also means that every question requires a unique approach. That both modern calculation-intensive algorithms and traditional models may be required. And that sometimes big data is necessary, but in other cases little and medium data can offer a good solution. But especially that Data Scientists must have broad and deep method knowledge and experience with the applications thereof.
- What works in which situation?
- How do you create support for a solution and what does that mean for the first step in the project?
- What role does a client have?
- How do you guarantee results?
- And in which way do you already take into account a possible implementation at the end of the project?
Extensive knowledge and experience in Data Science & Advanced Analytics
CQM has that deep and broad knowledge and experience of statistics, optimization and software engineering. But especially with thousands of applications, with hundreds of very different clients. We can definitely do something for you!
For a no-obligation introduction, contact: Jacob Jan Paulus.
What makes CQM a specialist in data science?
- Over 40 years project experience with data science.
- We employ 40 data scientists with a minimum of an academic degree in Mathematics, Econometrics and/or Computer Science.
- There is intensive collaboration with clients, through optimal use of existing domain knowledge, to create sustainable solutions that address the client’s specific questions.
- CQM has delivered some 4,000 data science projects for companies such as Philips, ASML, NS, ProRail, Albert Heijn, AgroEnergy, Cosun, Agrifirm, TenneT, Den Hartogh, Océ, Rijkswaterstaat.
- Where necessary, we work together with partners to come up with the best possible solutions.
