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Big Data and Data Science: Future Skills for IT Engineers

In order to gain a competitive advantage, all employers from all economic sectors are concerned by Big Data and mainly by new experts entering the market.

In the heart of this digital world, economic and citizen revolution where our individual information is exploited and sold, the Big Data market explodes. The industry is not ready to know the crisis. No sector seems to be able to escape from this revolution. To make this shift, large companies, SMEs or start-ups are working hard to recruit a myriad of competent experts to support their digital transformation.

In order to establish their competitive advantage, all employers from all economic sectors are concerned by this sector and mainly by new experts entering the market. However, if the first to recruit are from digital services, banking and insurance, the health sector is not left with the desire to see the emergence of a predictive, preventive, personalized and participatory medicine. Eventually the phenomenon will extend to the entire industrial sector: transport, energy, nuclear…

Back in 2012, the Harvard Business Review called the job of data scientist “the sexiest of the 21st century”. Demand is focused on profiles with dual skills in algorithmic and programming as well as a deep-rooted understanding of business issues. However, if these talents are highly coveted by recruiters, there is a significant number of junior profiles. This observation is the result of the formations that, as yet non-existent a few years ago, are multiplying today. In order to meet the growing demand, engineering schools do not hesitate to offer specialized programs.

Another profile that stands out is the data engineer, highly prized by all structures. The latter develops and maintains systems for collecting, storing and making available data. If, like the scientist, the demand for engineer profiles is important, the current offer is far from sufficient to meet recruiters’ expectations. The scarcity of candidates can be explained by the fact that this profession may seem still moving and does not yet meet the reputation of the scientist. Added to this is a shortage of developers faced with growing demands and different structures. The plurality of profiles is not appropriate.

If Big Data cannot be described as a technological revolution, a real general awareness of the amount of data that is now available to businesses and communities takes place. Companies are convinced of the importance of analyzing large amounts of “old” and “current” data to optimize the future and better customize products and services. Open Data makes it possible to learn more about the customer, his environment and to better target his issues, his consumers or his prospects.

In this dynamic and to go even further, Artificial Intelligence (AI) represents a considerable stake to answer the different entrepreneurial challenges of tomorrow. If it is necessary to abandon the fantasies of AI capable of competing or even supplanting the human intellect, autonomous algorithmic entities would make it possible to maximize content analysis.

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