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.

EFMD MASTER OK

This program has achieved EFMD accreditation, the leading international system for quality assessment, improvement and accreditation of business programs.


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. 2023/2024

GEOGRAPHICAL ORIGIN

ACADEMIC BACKGROUND

  • 26 y.o.

    AVERAGE AGE

  • 81%

    INTERNATIONAL STUDENTS

  • 20

    COUNTRIES REPRESENTED

  • 25%

    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 2024 – March 2025
  • Second term: March 2025 – June 2025
  • Internship: June 2025 – October 2025

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.

 

Miandar Toloue

The goal of the course is to introduce business intelligence (BI) platforms, with specific reference to data warehouses seen as an enabling technology for BI. Teaching will be mainly focused on OLAP, multidimensional modelling (at both the conceptual and logical level), and self-service BI. Some notions about data integration and cleaning will be provided.

Gallinucci Enrico
Rizzi Stefano

Today it is crucial to be able to use data for making better marketing decisions. This is possible by better understanding, predicting and managing customers’ behavior in a landscape where customers and brands (firms) are decision makers. This course focuses on the applied use of various techniques/methods, theories and approaches from marketing literature in practical business cases. In more particular words this means exploring, investigating and predicting behavioral and attitudinal (customer) data to provide data-driven answers to relevant marketing questions

Konus Umut

This course is a natural continuation of the Machine Learning course. It provides guidelines for running a Data Mining process and then discusses, with practical examples, the complete pipeline from data to machine learning concepts.
In particular, the following topics are covered:

  • 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.

Principles are introduced in class with presentation of slides and stimulating discussions with students. Methods are then applied with laboratory exercises.

 

Francia Matteo
Gallinucci Enrico
Sartori Claudio

The course aims to explore the principles of financial statement analysis. It provides the participants with a framework to understand how businesses’ value and risks are captured in financial statements and price them correctly.

Dal Maso Lorenzo

This course emphasizes statistical methods useful for tackling modern-day data analysis problems. A special attention is dedicated to techniques that help managers to make intelligent use of databases by recognizing patterns and making predictions.

The students will develope skills to:
• plan a statistical data analysis process
• manage a data source
• choose the best method to analyze the data
• implement the analysis and interpret the results

Camillo Furio
Farnè Matteo

The course will detail typical operations management issues by taking a quantitative approach for supporting decision-making processes. The main topics covered in the course will focus on the modelling and simulation of the organizational processes aimed at supporting companies’ strategy implementation. In particular, the course grounds on the principles of system thinking to help participants to model and to understand the dynamic interplay among people, decisions and resources involved in companies’ operations. The aim of the course is to hone decision-makers’ capabilities to capture the deep causal structure that generates events and phenomena thereby foreseeing long-term consequences of decisions and actions. In the course, participants will learn how to build a computer model of complex organizational processes in order to conduct “what-if” and scenario analysis.

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 technical capabilities of coping with text processing, text classification, sentiment analysis & opinion mining, transfer learning, using also deep neural networks, language models and explanation text mining.

Frisoni Giacomo
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

Artificial intelligence (AI) is a discipline whose goal is to realize this dream through the use of a wide variety of techniques, from logic-based symbolic computation to sub-symbolic models inspired by the structure of the brain, such as neural networks. This course will provide an introductory overview of the various existing artificial intelligence techniques, focusing on industrial applications, discussing future challenges and opportunities, and also addressing some of the social, economic, and ethical implications.

Gabbrielli Maurizio
Roberto Amadini

The aim is to provide 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 aspects (i.e. operation security) need to be considered.

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

This course provides an introduction to the basic principles and methods of Data Mining and Machine Learning, with emphasis on Classification, Clustering, Association Rules, Outlier discovery. Analysis of the main problems related to data quality and data transformation. Python will be used as part of the course to solve machine learning problems.

Sartori Claudio

Big Data is a big challenge in today’s world. Companies and public entities urgently need to manage the acquisition, presentation, sharing, analysis and visualization of data.

The first module starts with a general overview of the Data Revolution and Industry 4.0 and then jumps into the world of technologies and architectures provided by the main cloud and technology vendors. In the second part, the course explores how to use structured and unstructured data at their best, so to jump in the “AI world” to get insights to provide support to business decisions, with some case studies.

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

Srinivas Jagarlapoodi – India

Data Scientist, Panini
Master in Data Science and Business Analytics (A.Y. 2022/2023)

"The master's program was instrumental in my seamless transition from a neuroscientist to a proficient data scientist. The program's holistic, multidisciplinary approach, seamlessly blending theory with hands-on applications, elevated my technical skills and fostered personal growth. My transformative journey at BBS empowered me to excel as a Data Scientist while gaining insights into global perspectives through engagement with international students and faculty. To future students, I strongly recommend embracing the program's cultural diversity, actively participating in practical applications, and leveraging the expansive BBS network for a globally enriched, and business-savvy transformative experience."

Aish Kumar Jesrani – Pakistan

Senior Data Scientist, Iveco Group
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

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 Analyst, 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 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."

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."

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."

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.
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 and download the documents available in this section

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

Email: datascience@bbs.unibo.it

Martina Carissimi Junior Program Manager

Telefono: +39 0512090184

Email: datascience@bbs.unibo.it

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