“How the Da.Re. project is going on?”
“Which is the value brought by the research carried on in this first year?”
“Can we expect a valuable training course for Data Scientist, moving from this results?”
We asked Norberto Patrignani, associate lecturer at Politecnico of Torino, I3P and Catholic University of Milano, to give a critique of the research we performed in this first year of the Da.Re. project.
Norberto Patrignani is specialist in the areas of Ethics and Informatics and lectures in courses of study ranging from Statistics to Philosophy up to Business Management. This openness and wide sight in the panorama of Data Analysis makes him the right professional to critically review our First Intellectual Output.
“All over the world the digitalization process is pushing all organizations towards a new dimension where the tsunami of data generated by sensors (Internet of Things), data coming from connections among intelligent machines (Industry 4.0), and data related to the digitalization of all the processes inside enterprises risks to create an information overload without any value for organization themselves.
Indeed, this transition requires new skills and competences for collecting, storing, processing and visualizing interesting results from big data, useful in supporting management’s decisions and in translating this data into value.
The Da.Re. project is precisely addressing these needs.
In this First Intellectual Output, the partners of the Consortium describe, in their countries and at EU level, the situation related to big data. This interesting information will be useful to create new knowledge for designing and creating teaching and learning activities for covering these gaps.
The results could cover the entire scenario of big data:
- DATA FUSION: where is data? It is worth to collect all of it? How to collect this data? How to build a Data base Management System and a Data Warehouse?
- DATA ANALYTICS: How to process data? What are the best algorithms, programming languages? Are they based on traditional computing like programming or new “connectionist” approaches are needed like neural networks, machine learning, etc,?
- DATA VISUALIZATION: what is the best human-computer interaction design? What kind of managerial decision these data are going to support?
These results provides the Da.Re. Consortium with the foundation for a targeted development of the training modules needed.
This Intellectual Output provides useful background knowledge to all actors active in the “big data stakeholders network“: businesses, SMEs, industrial association, universities, training institutions and school, policy makers, young generations, students, and ICT vendors and software providers.”
What to say? We are doing our best to integrate the different competences of the consortium partners and it seems we are on the right track to create a valuable Data Scientist training course!