Disruptive Technologies
Open Innovation Campus
Disruptive Technologies
Are you interested?
If you are a professor or university student and you are interested in participating in the TUTORING program, register your information so that we can start the program.
Aimed at students looking to develop their TFG/TFM and who have a strong interest in new technologies, especially those related to root cause analysis techniques and Cloud technologies.
Strong proficiency in the Python programming language and basic knowledge of machine learning principles and an understanding of Cloud Computing tools and services, which will be fundamental in the development of the project, are recommended.
"Incident" is a word that is repeated almost daily in technology companies. We refer to it to indicate an anomalous situation in a development or behaviour, but what is the reason for this word?
Normally, we will see it rooted in the following expression: "We have to get to the root of this problem". This is also a phrase often used when trying to find a way to solve incidents. Issue management and resolution involves not only solving the immediate problem temporarily or permanently, but also identifying and addressing the underlying root cause of the problem.
The objective is to prevent such situations from recurring in the future. Without addressing the root cause, organisations run the risk of facing the same problems over and over again. This can lead to financial losses, damage to the company's reputation and even decreased customer satisfaction.
In an increasingly globalised and digitised world, where businesses are interconnected through complex supply chains and information systems, the ability to effectively address the root cause of a problem is essential. It is not just about fixing what is broken, but understanding why it broke in the first place.
Ultimately, effective problem management is the difference between a company that simply reacts to problems and one that anticipates and prevents them.
The challenge will consist of benchmarking the state-of-the-art baselines provided by the Academy, e.g. using technology, research datasets and developing deep learning approaches for the detection of root cause analysis in an operational scenario with several systems running.
It is recommended that the final paper incorporates the development of experimental software and documented report to assess the progress of benchmarking, use of the technology and the different approaches, etc. ...