Data Science and Business Analytics

Influencing with facts

GOALS

The Master in Data Science and Business Analytics is designed to provide highly specialized training for those who have developed a strong interest in data processing, and would like to hone that skill in terms of searching for facts that can influence the decision-making processes of a company. By applying some of the most innovative analysis methodologies available and using a wide range of instruments, the course lays the foundation for transforming raw data into operational information that can be used to resolve company problems requiring tactical or strategic decisions. The training involves a range of skills designed to bring out the three core competency areas: business economics, IT and, lastly, speculative analysis or statistical mathematics. One strength of the Master is that it is not limited to a specific company’s software; instead, participants can experience a range of programming and analysis tools, including open source software.


WHO IS IT FOR?

The Master in Data Science and Business Analytics is designed for young graduates with excellent knowledge of English, who want to learn how to manage a big data business, and are aware of the opportunity that this presents in terms of generating value. Their ability to interpret signals and get results sets them in good stead for a career in medium and large companies or consultancies, realizing their ambition to occupy strategically important roles.


CAREER OPPORTUNITIES

The course outline overlaps with a range of corporate functions; a linking position, placed within a team of experts responsible for company growth dynamics. With a view to increasing the impact of Data Science processes, the course includes a module dedicated to management communication techniques, which are vital if students are to become representatives capable of dealing with an organization’s senior management. Through the Master it is possible, once having completed in the companies the years of experience required, to access the following job positionsData Scientist, Data Analyst Consultant, Business Intelligence Manager.

If you would like to be at the forefront of a key sector for the growth of multinational companies, contact the master Program Manager.

 

SERVICES

Bologna Business School provides student support services included in the tuition fee for the Master.

 

In collaboration with:

Programme Advisory Committee:

  • Gildo Bosi – Head of R&D Automation, SACMI
  • Marco Breda – Head of Advanced Analytics & AI, Engineering
  • Lucia Chierchia – Managing Partner, Gellify
  • Stefano Da Col – CEO & Founder, Analytics Network
  • Lam Hoang – Research Staff Member, IBM Research Europe – Ireland
  • Sameer Rohadia – Business Intelligence Developer for Mobile App, Hannover RE
  • Jacopo Romagnoli – Head of Innovation and WEB3, VAR Group

 

Ranking

RANKED BUSINESS QS

QS Quacquarelli Symonds is the international network focused on services, analysis and in-depth reports of post-experience and university education, geared toward international mobility and career development. The QS Online MBA Ranking is based on insights from the business world and a methodology that allows programs to be evaluated according to four parameters: Faculty and Teaching, Class Profile, Employability and Class Experience.

 

Accreditation

EQUIS

Bologna Business School is EQUIS – EFMD Quality Improvement System accredited, one of the most important international quality assessment and continuous improvement systems for Schools of Management and Business Administration.


Claudio Sartori

Claudio Sartori

Director of Studies
claudio.sartori@unibo.it

" With this Master you will learn techniques used to manage, manipulate and analyze increasing amounts of data that trace and nourish the economic and social processes of today. You will also learn how these techniques can be effectively used in businesses for value creation and how the results can be effectively communicated and made available to recipients. "

CLASS PROFILE A.Y. 2022/2023

ACADEMIC BACKGROUND

GEOGRAPHICAL ORIGIN

PROFESSIONAL BACKGROUND

  • 27 y.o.

    AVERAGE AGE

  • 48%

    INTERNATIONAL STUDENTS

  • 12

    COUNTRIES REPRESENTED

  • 40%

    FEMALE STUDENTS

Structure

The Master in Data Science is a full-time program structured in 1,500 hours of learning activities over 12 months of study, divided into: 400 hours of lecturing, an estimated 600 hours of independent study, and 500 hours of internship.

The structure of the Master is divided into:

  • First term: October 2023 – March 2024
  • Second term: March 2024 – June 2024
  • Internship: June 2024 – October 2024

The Master offers a series of pre-courses at the start of the academic schedule: Software programming (Python), the foundations of data and SQL, basics in descriptive and inferential statistics, explorative data analysis and the fundamentals of economics.

Classroom participation is about 30 hours per week structured in order to allow time to work in groups, while not neglecting individual students focus and management of interpersonal relationships.

COURSES

The laboratory work plan addresses the complete process of data analysis, starting with loading data using different approaches and developing models for analyzing and visualizing the results. It will study some programming languages (as R, Python and TensorFlow) with reference to their specific use in High Performance Computing (HPC). In this context it will use libraries for parallel computing (H2O) and libraries for Deep Learning (Keras).

It will cover also software for the creation of graphic Workflow for Data Analytics, as Knime and Orange. The work plan provides for the developing of a project during a Kaggle competition at the end of the course.

The course is coordinated by Giorgio Pedrazzi and will be hold by CINECA staff, the largest Italian computing centre (Dipartimento Super Calcolo, Applicazioni e Innovazione and Laboratorio Big Data e Analytics).

Pedrazzi Giorgio

The course focuses on data protection law. After a brief overview of the Italian and European framework, the course will focus on the new General Data Protection Regulation, applicable all around Europe since May 2018. The course aims at exploring the relevant obligations of controllers and processors. Specific attention will also be paid to conditions of lawfulness of the processing, data subjects’ rights and controller’s accountability.

 

Zanni Sara

This course explores the following topics: Business intelligence (BI), motivations, objectives, definitions and solutions. Data warehousing as an enabling technology for BI: architectures, techniques and methodologies of On-Line Analytical Processing (OLAP) for data analysis. Multidimensional modeling with the Dimensional Fact Model (DFM). Self-service BI platforms. Relational OLAP. What-if analysis. Laboratory exercises on OLAP, DFM and self-service BI.

Gallinucci Enrico
Rizzi Stefano

The new priorities of marketing management: the marketing metrics and dashboard indicators of marketing.  From the value for the customer to the value of the customer: customer value, satisfaction, loyalty and customer equity. Analysis, measurement and management. Customer Relationship Management: acting on acquisition, retention and development. Big Data and Customer Insight Management. Customer insights and Big Data for improving marketing decisions and management. Marketing Modeling and Marketing Analytics.

Konus Umut

Models and methods for knowledge extraction from databases. Study of different types of data and methods of pre-treatment. The functions of Data Mining. Supervised and unsupervised learning. Algorithms and methods for constructing classification models. Clustering algorithms. Algorithms for discovering association rules. Methods for evaluating the quality of data mining results. Data mining laboratory in order to apply the studied methods.

 

Francia Matteo
Sartori Claudio

This course provides students with a deep understanding of the following topics: the reference model. The analytics for understanding the pattern and the business dynamics of an enterprise. Business process analytics, market, custodian and supply chain analytics; analytics of competitors. Financial cost and revenues analytics. The use of business analytics in the design of systems for measuring the company’s performance.

Dal Maso Lorenzo

This course explores the following topics: Univariate analysis: Distributions of quantitative and qualitative traits. Summary indicators: average values and variability indices. Data transformations. Graphical representations. Association between variables: Connection, covariance, correlation. The linear regression model. Elements of probability calculation: Probability (Binomial, Poisson, Normal). Signals of statistical inference: confidence intervals and hypothesis testing. Analysis of multidimensional data: Matrices of data, variance and covariance, correlation and dissimilarity. Laboratory exercises with dedicated software.

Camillo Furio
Farnè Matteo

The course will explore and analyze typical problems associated with operations management and address them through quantitative modeling in support of decision making. The issues will be handled by combining a business-oriented approach with quantitative methods on a statistical and econometric basis. The main contents are related to: management of production capacity, inventory management and control, service operations, selection and monitoring of suppliers, process optimization and simulation. The main objectives of the course relate to the ability to model complex business situations and to analyze them through technical and quantitative tools designed to monitor and improve business performance, teams and individuals.

Mollona Edoardo

The goal of the course unit is to present theoretical and practical aspects of text mining regarding text classification and sentiment analysis & opinion mining.

The learning outcomes are the capability acquisition of cooping with problems of text classification and sentiment analysis & opinion mining

Moro Gianluca

The course analyzes the legal framework of the rights of the person when dealing with technology, the protection of personal data, the intersection between person and market in the face of technological platforms and big data, the normative references of GDPR, Digital Service Act and other legal formats with a global vocation. Attention will be paid to the ethical challenge underlying the balance between human intervention and artificial intelligence, to the comparison between legal language and algorithms from the applicability of models to the role of law and regulation in the face of technological change and to the governance and risk management of data.
Some insights concern automated decisions, profiling in the credit and in the insurance sector and the coexistence between incumbents and new entrants in the financial sector.

Manes Paola

The course discusses some relevant themes related to blockchain technologies, cryptocurrencies, ICOs, smart contracts and novel applications that can be built over the blockchain. Bitcoin and novel cryptocurrencies gathered momentum in the last months. More and more investors look with interest at these technologies, while others label them as a dangerous speculative bubble. The truth is that the blockchain, and the alternative implementations of a distributed ledger, represent very innovative technologies, that can be exploited to build novel distributed applications. Moreover, the possibility of creating smart contracts, running on top of the blockchain, permits trusted interactions and agreements among different (and possibly anonymous) parties, without the need for a central authority. This course will illustrate the main principles and conceptual foundations of the blockchain and smart contracts.

Ferretti Stefano

The course focuses on the finance aspects following the life cycle of young and innovative ventures from their start-up. These young ventures usually require substantial outside financing in early stages to eventually create employment, growth, social contributions and tax revenues in their future. Bank financing is hardly available for these ventures and therefore, all funds need to be raised from other sources, e.g. friends and family, business angels, or from professional financial intermediaries, so-called venture capital and private equity funds. Besides those traditional channels, ventures can raise funds from “the crowd” using digital platforms (crowdfunding) or blockchain-based technologies (ICOs).

Groh Alexander

The digitization of the economy is one of the most relevant issues of our time. The objective of this course is to analyze how digital economy has fundamentally challenged traditional business models and created new business opportunities. We will start with a brief introduction of the digital economy and then analyze the specific business strategies adopted by the different players in this ecosystem, specifically platforms. We will also discuss the implications for public policy and regulation. In particular, we will consider whether new business practices and contracts in the digital economy are beneficial or detrimental to society. Real case studies related to Amazon, Airbnb, Booking.com, Facebook, Google, Uber, and others, will be analyzed.

Mantovani

Since the first mechanical automations of the 17th century, one of the great dreams of the humanity has been the construction of machines exhibiting human behaviors and intelligence. Artificial intelligence (AI) is a discipline whose goal is to realize this dream by using the most different techniques, from symbolic computation based on logic to sub-symbolic models inspired by the structure of the brain, such as neural networks.

The last few years have witnessed a sensational exploit of AI applications in many different fields – with a relevant growth of investments – inducing many experts to believe that the dream will come true in a short time.

This is inducing many companies to reconsider their business strategies and, more generally, requires a deep rethinking of several crucial aspects of our society.

The course will provide an introductory overview of the various existing AI techniques, focusing on their industrial applications, discussing future opportunities and challenges, touching also on some social, economic and ethic implications.

Gabbrielli Maurizio
Roberto Amadini

It’s undeniable that mankind strive to build unbreakable systems, even if human history has demonstrated so far that this is nothing more than a myth. The real world is mainly made of fragile systems, so that reality is much different from the expectations.

The goal of this course is to provide a basic knowledge concerning the main concepts and principles of computer security (e.g. risk, tools for risk assessment and evaluation, attacks and their typical structure, resources, functional systems requirements, human component). In this way, the course will provide the basic tools for the design and implementation of reasonably secure systems. During this process, either methodological, technological and behavioral (i.e. operation security) aspects will be considered.

After the course, the students should be able to critically evaluate the security of a (computer) system considering both the system as a whole and its main separated components (e.g. authentication and authorization mechanisms and procedures). They will also be able to find the main vulnerabilities of such a system and to identify the more appropriate countermeasures to allow the mitigation of vulnerabilities and reduce the risk to an acceptable level.

The goals described above will be obtained not only by teaching some of the main theoretical aspects of computer security but also by describing and discussing many real world examples in detail.

 

D’Angelo Gabriele

The course is focused on understanding of the opportunities arisen from digital transformation, in terms of innovative business models for companies and new value for users. Specifically, the course will deepen technology forecasting and technology roadmapping methodologies, applied to emerging digital trends, focusing on Fintech, IoT and Artificial Intelligence.

Meoli Azzurra

The course provides an overview on the Machine learning field, with a particular emphasis on
symbolic learning techniques (sub symbolic techniques will be covered by the course on Neural Networks).

The main learning problems and paradigms will be introduced along with examples explaining how to
use the learned models into decision support systems.

Application areas that will be covered have industrial impact in fields as automotive, energy management,
predictive maintenance and policy making.
The course will cover both lectures and hands-on sessions.

Sartori Claudio

The digital revolution has led to an explosion in the amount of available data and information (Big Data), the ability to analyze and correlate this information is becoming a fundamental element to an enterprise’s competitiveness and a new source of economic value and innovation. Big Data, however, is unable to be managed properly by using traditional instruments of Information Technologies because of their size, their heterogeneity and their many peculiarities. For this reason, new architectures, methodologies and tools are being created for data scientists to transform this data into value for the company and to support the decision-making process. This course will analyze the various types of data available, technical access to information, methods to handle them and the architectures and tools to store and process them.

Baffetti Federico

Neural networks are a class of machine learning algorithms, originally inspired by the brain, structured in layers of interconnected artificial neurons.

The network can be trained on data to optimize its connections to a specific task.

 

Deep neural networks, that is networks with multiple internal (so called hidden) layers, have recently seen a lot of success at practical applications. They’re at the heart of production systems at companies like Google and Facebook for image classification, speech recognition, natural language processing, language understanding or robotics.

 

The course gives an overview of the foundational ideas and the recent advances in neural nets, explaining the potentialities of the topic for practical purposes. We shall cover supervised and unsupervised techniques, methods for visualizing and understanding the behavior on neural nets, as well as adversarial techniques to fool them. We shall also hints to recent applications in the field of reinforcement learning, and some amazing results in game simulation. 

Asperti Andrea

Learning approach

The educational sessions provide different learning methods, including lectures, simulations, discussions of case studies and presentations by companies, testimonials, and group work.
The curriculum is completed with master lectures held by professionals from the worlds of business, academia and politics, with opportunities for discussion and interaction with the business world through case histories.

Faculty

Faculty members at Bologna Business School work together offering outstanding teaching standards. An international and interdisciplinary approach is guaranteed by a joint team of distinguished national core professors, adjunct, visiting professors, guest speakers and top managers.

CAREER DEVELOPMENT

The integration with companies is a priority and an ever-present feature of all programs of the Bologna Business School, hence for the Master in Data Science too.

The School is fully committed to creating employability, by way of a systematic career service action, constantly focused on matching at best the students’ professional projects with the needs companies have.
The internship is an exceptional springboard, suffice it to say that six months after the end of the full-time masters at Bologna Business School on average 91% of students work in a company.
The BBS Career Service assists and supports students since the very beginning, along a training and professional development path. This is accomplished by organizing a series of workshops, with the aim of providing the fundamental tools and resources to be appropriately prepared for the labor market.

 

To achieve this goal, students are involved in several workshops, among which we may list:

  • Writing a CV and a Cover Letter
  • How to create an effective Linkedin profile
  • How to prepare for a job interview

 

In addition to this, thanks to the collaboration with professional career counselors, students receive a customized service, in order to understand their strengths and to build a professional development plan, which will turn out to be helpful when looking for an internship. Here follow some of the activities:

  • Initial guidance interviews
  • Specific interviews, focused on one’s own career plan
  • Continuous support to students with one – to – one sessions

P

Alumni

Aish Kumar Jesrani – Pakistan

Data Scientist, Iveco Group - Pakistan
Master in Data Science and Business Analytics (A.Y. 2021/2022)

"Coming from a business-focused background, this master's program provided me with a strong foundation to successfully transition into the data science field. The well-rounded curriculum struck the perfect balance between theoretical concepts and practical applications, while the engaging teaching methods fostered a supportive learning environment. The Career services team also played a crucial role in helping me leverage networking opportunities and secure a professional position in the Italian market and in my preferred field. Throughout my time at BBS, I had the pleasure of connecting with remarkable individuals who not only enriched my educational experience but also contributed to my personal growth. "

Sidorela Topi – Italy/Albania

Junior Data Scientist, Analytics Network
Master in Data Science and Business Analytics (A.Y. 2021/2022)

"The Master in Data Science allowed me to acquire skills that are increasingly sought after in the international job market, combining my financial background with statistics and machine learning through a highly functional approach and practical applications. Thanks to the BBS network I met wonderful people who enriched me with their culture and I got in touch with some of the most important Italian companies, where I got to know the company where I did my internship and where I currently work in the Data Science area."

Bassam Alkhatib – Jordan

Digital Data Scientist - Gucci
Master in Data Science and Business Analytics (A.Y. 2018/2019)

"The Master strikes the perfect balance between the required theoretical background necessary to establish a strong foundation in Data Science to build upon in my career in any direction, and the practical hands-on knowledge necessary to understand Data Science’s potential and applications in different settings. I benefitted in my studies here in many ways; I was taught and mentored by world-leading experts in the field of Data Science, I also made lifelong friendships with likeminded ambitious enthusiasts about this field from all over the world, and finally, being exposed to the Italian culture has been one of my most fulfilling experiences of my life. "

Calvin Omari – Kenya

Digital Specialist for the Regional Project for the Africa Minigrids Program, UNDP
Master in Data Science and Business Analytics (A.Y. 2018/2019)

"University of Bologna Business School opened my eyes to the expertise of Data Science with its top-class faculty members who not only guided us but delivered practical industry experience through coursework and internship, this has so far helped in me in my career as I have advanced to international assignments. The emphasis on Italian excellence came in handy and has been a great influence on my current role as a Data Analyst & Architect which demands precision and accuracy. The faculty and the networking off BBS community will always be a treasure to me."

Valerio Nicosia – Italy

Data Scientist Manager, Sky
Master in Data Science and Business Analytics (A.Y. 2016/2017)

"With a background in Corporate Finance and a great passion for statistics and the IT world, the Master in Data Science provided me with the best tools to work as a Data Scientist. Thanks to the BBS network I got in touch with some of the most important Italian and international companies, starting with the internship, that boosted my professional growth."

Valerio Trotta – Italy

Data Scientist, Sorgenia
Master in Data Science and Business Analytics (A.Y. 2017/2018)

"The Master in Data Science gave me the opportunity to deepen what I had learned during my previous studies in statistics and integrate it with my passion for technology. This experience has allowed me to make a career out of these passions. The strength of the program is the ability to train on technical aspects without losing the focus from what are the demands of the increasing number of companies that are riding the wave of the data revolution."

Sameer Rohadia – India

Business Intelligence Developer for Mobile App Development, Hannover RE
Master in Data Science and Business Analytics (A.Y. 2016/2017)

"After many years of industry and teaching experience in India, I approached the field of Data Science and I discovered the Master of BBS. The international dimension, helped me to interact with colleagues from different countries. Currently, I prepare contents and provide training programs in the area of Big Data and Advanced Analytics in Continental AG (Germany). BBS will always be close to my heart."

Daniele Frassineti – Italy

Senior Data Scientist, Novartis
Master in Data Science and Business Analytics (A.Y. 2015/2016)

"Today world is dynamic, old certainties are questioned and new opportunities are created. The Master in Data Science was the chance to catch these opportunities, opening up the doors for an extremely stimulant world. It allowed me to approach companies at the cutting edge of innovation. I started my career thanks to the knowledge gained at BBS."

COMPANIES

The goal of the Career Service is also to allow students to connect with national and international companies. Over the years, Bologna Business School has managed to establish a wide-ranging network and a sound partnership with leading companies in Italy, thanks to a personalized approach, based on each company’s needs. The collaboration features the following activities:

  • Sending CV Books
  • Sharing internship opportunities
  • Company presentations
  • Career days
  • Project works
  • In-class activities with case studies presented by Managers and/or HR professionals.

Moreover, companies support the Master in Data Science and Business Analytics with scholarships, professional opportunities, career fairs and company presentations.

The companies that worked with us in 2022/2023 are:

ACCENTURE ANALYTICS NETWORK ARTHUR D.LITTLE AUTOMOBILI LAMBORGHINI BAKER HUGHES BARILLA BIP BIT BANG BOOSTER BOX BPER CAMST CEFLA CHAMPION EUROPE CINECA COESIA CRIF DELOITTE DR. SCHAR ENGINEERING EY GRUPPO HERA ICONSULTING IVECO GROUP HAIER EUROPE HAVI HEINEKEN HILTI JAKALA KERING LIU JO LUXOTTICA MUSIXMATCH MY THERESA NTT DATA PANINI PIAGGIO PHILIP MORRIS INTERNATIONAL PWC SAFILO SCHNEIDER ELECTRIC SAVINO DEL BENE SEFORALL SIDEL SKY SORGENIA TETRAPAK TOYOTA MATERIAL HANDLING TESLA TXT GROUP VERSACE VERTIV VODAFONE WELLMICRO

FEES

The tuition fee for the Master is 14,800 euros (VAT free) to be paid in three installments:

  • First installment: 1.850,00 euros
  • Second installment: 7.000,00 euros
  • Third installment: 5.950,00 euros

The fee includes participation in the Master, all the study material available through the online platform, and access to the services and facilities of  Bologna Business School such as: personal account for the BBS wi-fi, use of the PCs in the Computer Lab, access to the study areas, access to the internal gym, special rates for the School restaurant.
Furthermore, the fee gives participants the right to take advantage of the supporting activities of the School, such as the language courses and the master lectures by invitation. Free parking is also available within the BBS campus.

Additionally, with the Student Card of the University of Bologna, students have access to all of the university facilities, including over 100 libraries, digital resources and study halls (including databases and online subscriptions); the three city center canteens and all university student related discount offers. More information is available on the site of the University of Bologna: http://www.unibo.it/it/servizi-e-opportunita

SCHOLARSHIPS

At Bologna Business School we understand the importance of financial aid in supporting our students to achieve their educational goals. We are aware that an advanced, high quality training path can be a significant commitment but we also truly believe that investing in one’s future always pays back.

 

Bologna Business School is pleased to offer partial scholarships of 6,000€ and 4,000€ available to the most deserving students. The scholarships will be awarded on the basis of merit criteria to the students occupying the highest positions after the selection process. The highest ranked students will be those with not only a solid academic and/or professional background, but also those who have proven to be the most motivated to participate in the course. The winners will be informed at the time of the admission.

REQUIREMENTS

In order to be admitted to the Master’s course you must have:

  • Bachelor’s degree (obtained within the closing date of enrollment of the selection round in which you participate)
  • Excellent level of English

The admission to the Master is subject to the positive evaluation of the selection test in line with the number of places available. The selection process consists of one Aptitude Test and one English Language Test, both prerequisites to be admitted to the motivational interview in English.

APPLICATION PROCESS

  1. Register on “Studenti Online” by connecting to the site studenti.unibo.it
  2.  Select “First Level Master”
  3. Pay the participation fee for the selection (60 euro for each Master)
  4. Upload the required documents online:
  • Curriculum Vitae in English
  • Motivational letter in English
  • Letters of reference in English (optional)
  • Photograph of recognition
  • Front and back ID/passport
  • If available, a GMAT/GRE certificate with a score above 550 (GMAT) or equivalent (GRE). Applicants uploading this certificate are exempted from the written aptitude test as part of the admission process.
  • If available, an English language certificate (TOEFL, IELTS or CAMBRIDGE) attesting a minimum English level of B2 in the European framework. Applicants uploading this certificate are exempted from the written English test as part of the admission process.
  • For degrees obtained in Italy: Self-certification of Bachelor’s degree with details of exams taken and relative grades
  • For degrees obtained abroad: Dichiarazione di Valore (to be requested at the Italian Embassy in the country where the degree was obtained) or Diploma Supplement (to be requested at the university where the degree was obtained). In the event that the candidate is unable to obtain the Dichiarazione di Valore or Diploma Supplement at the time of enrollment, he/she may temporarily replace it with a Conditional Enrollment Form, which will be sent after enrollment by datascience@bbs.unibo.it.

For further guidance, students who obtained a bachelor’s degree abroad are encouraged to check the page below: https://www.unibo.it/en/teaching/enrolment-transfer-and-final-examination/declaration-of-value-translation-and-legalization

For further information concerning the selection process and the related documents we invite you to consult the Master details here and download the following documents.

CALL FOR APPLICATION INSTRUCTIONS TO APPLY TO THE SELECTION CONDITIONAL ENROLLMENT FORM

CONTACT US

     
     

DOWNLOAD BROCHURE

     
     

Book an appointment

     
     
Contact us
Federica Giannattasio Program Manager

Telefono: +39 0512090132

Whatsapp/Viber: +39 3357241860

Email: datascience@bbs.unibo.it

Martina Carissimi Tutor

Telefono: +39 0512090184

Whatsapp/Viber: +39 3357241860

Email: datascience@bbs.unibo.it

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