NECESSARY PROFESSIONAL FIGURES FOR A BIG DATA PROJECT
The 2018 edition of the Observatory focused particularly on competences, as the lack of skills remains the main brake on the development of Big Data Analytics planning.
“The lack of skills in the field of Data Science – recalled Alessandro Piva, Head of Research – and more generally in the ability to manipulate data, characterizes the phenomenon of Big Data since its dawn”.
To demonstrate this, 77% of large companies declare an undersizing in terms of human resources dedicated to Data Science.
“In addition to the imbalance between supply and demand, companies clash with the search for not standardized roles, whose core skills are not known. For this reason, the 2018 Research – Piva explained – deepened the theme of the professional figures not only through the dissemination data, but also through the analysis of job offers present on Linkedin, in order to obtain more qualitative insights on the main skills and activities carried out”.
These are the main evidences that emerged:
Data Scientist – The figure of the Data Scientist is concretely entering in the daily activity of many companies. In 2018, the data on the dissemination of this role within large organizations recorded a further, albeit slight, increase. The large companies that have at least one figure of Data Scientist inside, formalized or not, are 46% (+ 1% compared to 2017).
Data Engineer – The extraction and delivery of insights are bound to a series of preliminary activities consisting in the design of the infrastructure and in the construction and maintenance of the data pipeline. These operations are the responsibility of the Data Engineer, a role of absolute importance, long underestimated in favor of the more popular Data Scientist. In 2018, 42% of large Italian companies claim to have an internal data engineer.
Data Analyst – The Data Analyst, which deals with researching quantitative evidence within large amounts of data, so to support business decisions, is present in 56% of large Italian companies and about half (44%) of companies that do not yet have this figure expect to enter it by 2019.
(From “How to do big data analysis and get value for companies” – www.zerounoweb.it)
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