16 NOV 2017

Big Data Professions

With the evolution of information systems and with the growing need to organize large amounts of data, we need experts who are able to analyze, manage and support companies in cataloging, analyzing and reading data.

Moreover, the amount and types of data on the network grow exponentially as do the number of devices connected to the network. When data volumes increase, the need to catalog, analyze and process this data increases, for which traditional methodologies of analysis are not always indicated. Working and analyzing large volumes of data, processing it quickly for Business or Marketing needs, cataloging the different formats and extracting relevant information from these analyses is a necessity that becomes more and more concrete and urgent for various types of companies.

For this reason, new professional profiles emerge as well as job offers for those profiles. More and more frequently we find requests for Data Scientists, Data Architects, Insight Analysts, Data Engineers and Data Visualization Experts. What are the characteristics of these profiles? What training courses and what skills are required for the tasks to be performed in the processes of analyzing and cataloging data?


The Data Scientist acquires, analyzes, stores and interprets data in order to provide useful information to define business strategies. He knows statistics, computer engineering, data mining and statistical machine learning.

The position of Data Scientist is important in the company because current ICT companies are opening themselves to a greater awareness of the use of data and the competitive advantages that can be obtained by analyzing it.

Data Scientist, what training and skills are required?


The Data Scientist has a scientific educational path (degree in mathematical-statistical subjects, in engineering or in computer science). Very solid computer skills, a good understanding of technological aspects and business processes are required. In recent years, companies and universities, in synergy, are trying to create specific study paths for this profession.


The Data Scientist knows the origin of the data being analyzed and the possible distortions inherent in it, as well as recognizing which data is to be extrapolated and that which needs to be ignored because it is useless. The Data Scientist works with data, but also, has managerial and technical skills: this person knows the advantages and disadvantages of the tools analysis, and thoroughly understands the reference contexts and business areas; this person is able to design automated applications to suggest decisions in complex environments and communicates with the top management. The Data Scientist has good problem-solving skills and is creative and curious. In large companies this person interfaces with the board of directors and the heads of the divisions, in SMEs he or she interacts mainly with the owners or with the CEO.


The Data Architect is a figure with a precise role: design information systems dedicated to data, focusing on how and where to save data in such a way that it is available when needed. The Data Architect does not analyze data but structures and manages it so that those who have to analyze it, can easily find it.

Data Architect, training and skills for a high-level profile


The Data Architect has at least a bachelor’s degree in computer science, computer engineering or equivalent. The course of study must include disciplines related to data management, programming, analysis of systems and architectures. To gain access to senior positions, a master’s degree is recommended.


The Data Architect must know relational and NoSQL databases, software to manage data in databases, predictive analysis, data mining and programming languages. Furthermore, the Data Architect must have good problem-solving skills, as well as communication skills to interact with management and other figures in the company. Specifically, within a company, the Data Architect interfaces with management, with the Data Scientist and with the personnel involved.


The Data Architect uses statistical analysis tools on a large amount of data to obtain information that drives customers to purchase and inspires loyalty. For this reason, he or she interfaces with marketing and product divisions.

Insight Analyst, training course and professional skills


The Insight Analyst must have at least a bachelor’s degree in statistical sciences or equivalent.


The Insight Analyst has skills in statistical analysis programs such as SQL, SAS and SPSS. At the highest level of specialization, the Insight Analyst also knows the programming languages ​​Python and R. A professional who holds this role in the company must have an orientation to problem solving and must be able to understand customers and their needs.


The Data Engineer collects, stores and processes the data of a company to facilitate its analysis. Initially this person used relational databases to manage data archived in the form of tables, but today these structures are no longer sufficient, and the Data Engineer has to create and administer structures capable of handling large and complex data quantities with NoSQL databases such as MongoDB. Many companies use Hadoop framework and advanced tools such as Hive, Pig and Spark, but the range of existing structures available to a Data Engineer is very large.

Data Engineer, training and skills to work in a company


The Data Engineer has a degree in computer science, computer engineering and equivalent.


The Data Engineer interfaces with both structured and unstructured data and uses his or her expertise to understand how to interpret data based on the characteristics of the matrix itself. The Data Engineer knows programming languages ​​such as C#, Java, Python, Ruby, Scala and SQL. In the company, the Data Engineer interfaces with Data Scientists who deal with queries and algorithms for predictive analysis, with the business units and the various departments to provide a set of data to executives, and with business analysts for analysis and research of different types.


The Expert in data visualization is a technician who takes care of the data yield, that is the form that data acquires in order to be understood. At the same time, this figure must also be able to perceive the intrinsic value of data. Today, a Data Visualization Expert is among the most requested figures thanks to the diffusion of dashboards and data visualization tools. In the company, an expert in data visualization interacts above all with the Data Scientist, the first user of his work on data.

Expert in data visualization, training path and required skills


Expert in Data Visualization has a degree in computer science, statistics, mathematics and equivalent.


The Expert in data visualization must have skills in the use of data analysis platforms such as Tableau, Qlikview/QlikSense, SiSense and Looker. In addition, they must be able to use tools such as d3.js for creating and presenting interactive visual representations. A technical profile like this, deals with transforming complex data into graphs, tables and diagrams of various types, so that it is easier to understand them.

Edited by Lucia D’Adamo, supervised by Marco Pirrone