Data Science and Business Analytics

Influencing with facts

The Master in Data Science 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 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.

People who enrol in the Master in Data Science 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.

The Master is structured into two terms of classroom-based lessons in English and 600 hours of work experience over a total of 12 months. 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.

Thanks to the innovative technologies of BBS you can follow the master online as well.

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

THE MASTER IS AN INVESTMENT.
THE HONOR LOAN IS THE WAY TO FUND IT.


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In collaboration with:

Programme Advisory Committee:

  • Gildo Bosi –Responsabile R&D Automation, SACMI
  • Marco Breda – Head of Advanced Analytics CoE, Engineering
  • Lucia Chierchia – Managing Partner, Gellify
  • Stefano Da Col – CEO & Founder  Analytics Network
  • Sameer Rohadia – Data Analyst & IT Trainer, Freelance
  • Jacopo Romagnoli –Innovation Manager, VAR Group

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. "

ACADEMIC YEAR 2020/2021

Academic Background

Professional Background

Geographical Origin

  • 28 y.o.

    AVERAGE AGE

  • 43%

    INTERNATIONAL STUDENTS

  • 12

    COUNTRIES REPRESENTED

  • 9%

    FEMALE STUDENTS

  • 2 years

    AVERAGE WORK EXPERIENCE

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: 360 hours of lecturing, an estimated 540 hours of independent study, and 600 hours of internship.

The structure of the Master is divided into two terms:

  • First term: November 2021 – March 2022
  • Second term: March 2022 – June 2022
  • Internship: June 2022 – November 2022

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 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.

Ravaldi Federico

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.

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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.

 

Mura Matteo

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.

 

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.

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
Mignani Stefania

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 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.

Stefano Pio Zingaro

This course is
focused on the analysis of marketing technologies: how do they work? Why is it so important to collect data on the behavior of people online? What kind of tools and technologies are needed to collect and analyze data from digital properties and advertising?

Pellicciari Alessandro

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.

Andrea 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.

The approach and the tools learned during this course are prerequisites for the following “Cryptographic Protocols” and “Computer, Network and Cloud Security” courses.

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.

Chierchia Lucia

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.

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

 

Trough the Master in Data Science it is possible, once having completed in the companies the years of experience required, to become a Big Data Manager or a Web Analyst.

 

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Alumni

Bassam Alkhatib – Jordan

Digital Analyst – Max Mara Fashion Group
Master in Data Science (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

International Consultant - Data Analyst and Architect, World Food Programme
Master in Data Science (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, Axpo Italia
Master in Data Science (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, Deloitte
Data Science (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 my career at Engineering Ingegneria Informatica, to finally land in Deloitte Italia."

Sameer Rohadia – India

Data Analyst & IT Trainer, freelance
Master in Data Science (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

Data Scientist, Novartis
Master in Data Science (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."

Lorenzo Cellini – Italy

Solution Architect & Data Scientist, NiEW
Master in Data Science (A.Y. 2015/2016)

"The Master in Data Science provides you with skills and a mindset that are essential if you aspire to become a Data Scientist. The faculty is composed by numerous experts of the sector, capable of providing you with their academic knowledge and above all, with practical experiences directly coming from the professional world. These aspects make the experience unique and extremely interesting."

Elena Cipressi – Italy

Solutions Architect, Amazon Web Services
Master in Data Science (A.Y. 2015/2016)

"This is an educational path which connects people, expands knowledge and improves your academic background; there are countless sources from which you can deduce the role of Data Scientist. This Master adds one more dimension: the human one, by giving everybody the opportunity to customize it with critical thought, thanks to the continuous interaction between students, professors and professionals."

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 the CV book
  • Sharing internship and work opportunities
  • Presentations at the School premises
  • Career Day
  • Implementation of project works
  • Class-room activities with case studies presented by managers and/or HR professionals

 

Our partners are the foremost supporters of our students, with the provision of scholarships, internships and professional opportunities.

Bologna Business School’s partner companies for the Master in Data Science are:

ACCENTURE ALSTOM AMPLIFON ARETE' ANALYTICS NETWORK AUTOMOBILI LAMBORGHINI BANCA INTESA SANPAOLO BANCOMAT BIP BOOSTER BOX BORSA ITALIANA (LONDON STOCK EXCHANGE GROUP) BOSCH BUCCI INDUSTRIES CEDACRI CINECA CRIF CSE DATALOGIC DEVEYES GROUP DOXEE DUCATI ELECTROLUX ENGINEERING EXPERT SYSTEM FAAC GELLIFY GENERALI GROUP M GRUPPO CURA HERA HORSA ICONSULTING IGENIUS ILLUMIA ING KANTAR CONSULTING MAX MARA FASHION GROUP MUSIXMATCH NTTDATA NUOVAMACUT OPTIT ORACLE PHILIPS PIRELLI PROMETEIA PUBLICIS GROUPE RE2N SCHNEIDER ELECTRIC SCM GROUP SCS CONSULTING SHOPFULLY SIDEL SUPERMERCATO24 SYSDATA UNICREDIT UNIPOL VINHOOD VODAFONE WEBRANKING YOOX NET-A-PORTER GROUP

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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

HONOR LOAN

Participants are eligible to apply for Honor Loan with subsidised rate up to the complete coverage of the application fee.
For more information please mail to datascience@bbs.unibo.it

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 to the most meriting students. All of these scholarships are merit-based and will be awarded to the top-ranked candidates in the selection process. The students who come out on top in the selections will be students who not only come from strong academic or practical backgrounds but also those who display the strongest motivation to take part in this program.

There are scholarships of 6,000 euros and scholarships of 4,000 euros. All applicants will be considered for a scholarship – no specific application is required. The scholarships are awarded over the course of every round of selection and if you have performed well enough to merit one of them, you will be informed at the moment of admission.

The scholarships act as tuition waivers, so that they result in a deduction of the total amount of the tuition fees due.

 

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 tests in line with the number of places available. The selection tests consist of a motivational interview in English and a logic test in English.

APPLICATION PROCESS

  1. Register on “Students 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
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 guidance, we advise all students to read carefully the instructions indicated in the “call for applicants” and “operating instructions” files downloadable below.

Call for Applications 2021-2022 Introduction to apply for the Selection

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.

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