Program Overview

Màster Universitari en Data Analytics for Business

The Master's in Data Analytics for Business is a program designed to provide students with the skills and knowledge necessary to extract, process, and interpret large datasets, and to apply this knowledge in a business context.

Presentation

The program is aimed at students who want to develop their skills in data analysis and business intelligence, and who wish to pursue a career in this field. The program is designed to provide students with a comprehensive understanding of the concepts and techniques of data analytics, as well as the ability to apply these skills in a practical setting.

Objectives

The objectives of the program are:

• To provide students with a comprehensive understanding of the concepts and techniques of data analytics
• To equip students with the skills and knowledge necessary to extract, process, and interpret large datasets
• To provide students with the ability to apply data analytics skills in a business context
• To develop students' critical thinking and problem-solving skills

Target Audience

The program is aimed at students who have a background in economics, business administration, marketing, mathematics, physics, or engineering. It is also suitable for professionals who wish to develop their skills in data analytics and business intelligence.

Admission Requirements

To be admitted to the program, students must meet the following requirements:

• Hold a bachelor's degree in a relevant field
• Have a strong academic record
• Demonstrate proficiency in English
• Submit a personal statement and letters of recommendation

Program Structure

The program is divided into three modules:

1. Data Analytics: This module provides students with a comprehensive understanding of the concepts and techniques of data analytics, including data visualization, machine learning, and statistical analysis.
2. Business Intelligence: This module focuses on the application of data analytics skills in a business context, including business strategy, marketing, and finance.
3. Project Management: This module provides students with the skills and knowledge necessary to manage projects and teams, including project planning, risk management, and leadership.

Assignatures

The program includes the following assignatures:

• Fonaments de Big Data: This assignature provides students with a comprehensive understanding of the concepts and techniques of big data, including data storage, processing, and analysis.
• Visualització de Dades i Elaboració d’Informes: This assignature focuses on the visualization and presentation of data, including data visualization tools and techniques.
• Introducció a Python: This assignature provides students with a comprehensive understanding of the Python programming language, including data structures, file input/output, and data analysis.
• Processament amb Bases de Dades SQL: This assignature focuses on the use of SQL databases for data storage and analysis.
• Anàlisi Exploratòria de Dades: This assignature provides students with a comprehensive understanding of the concepts and techniques of exploratory data analysis, including data visualization and statistical analysis.

Assignatures Optatives

The program includes the following assignatures optatives:

• Fonaments d’Estadística per a l’Anàlisi de Dades: This assignature provides students with a comprehensive understanding of the concepts and techniques of statistics, including probability, inference, and regression analysis.
• Anàlisi de Dades per a la Salut: This assignature focuses on the application of data analytics skills in the healthcare sector, including health data analysis and health informatics.
• Anàlisi de Dades per a Màrqueting i Recursos Humans: This assignature provides students with a comprehensive understanding of the application of data analytics skills in marketing and human resources, including customer segmentation and talent management.

Professorat

The program is taught by a team of experienced professionals and academics, including:

• Ana Freire: Senior Lecturer at UPF-BSM and Vicedegana d’Impacte Social i Innovació Acadèmica.
• Alexandra Abós Ortega: Lecturer at UPF-BSM and Faculty, Operations, Technology & Science.
• Alberto Lempira Guevara Chacon: Teaching Assistant at UPF-BSM and Coordinador Acadèmic.
• Jorge Pereira Gude: Senior Lecturer at UPF-BSM and Senior Lecturer.
• Nia Plamenova Djourova: Lecturer at UPF-BSM.

Metodologia

The program uses a combination of teaching methods, including:

• Learning by doing: Students work on real-world projects and case studies to develop their skills and knowledge.
• Simulacions pràctiques: Students participate in simulations and role-playing exercises to develop their critical thinking and problem-solving skills.
• Tallers amb professionals del sector: Students attend workshops and seminars led by industry professionals to gain insights into the latest trends and best practices in data analytics and business intelligence.

Avaluació

The program uses a combination of assessment methods, including:

• Avaluació continuada: Students are assessed throughout the program through a series of assignments and projects.
• Examen final: Students sit a final exam at the end of the program to demonstrate their knowledge and skills.
• Treball final de màster: Students complete a final project that demonstrates their ability to apply the skills and knowledge they have acquired during the program.

Eines

The program provides students with access to a range of tools and resources, including:

• Treball de Final de Màster: Students have the opportunity to work on a real-world project that demonstrates their ability to apply the skills and knowledge they have acquired during the program.
• Un mentor personal: Students are assigned a personal mentor who provides guidance and support throughout the program.
• Recursos digitals: Students have access to a range of digital resources, including online libraries and databases, to support their learning.

Sortides professionals

The program provides students with a range of career opportunities, including:

• Data Analyst: Students can work as data analysts in a range of industries, including finance, healthcare, and marketing.
• Advanced Analytics Consultant: Students can work as advanced analytics consultants, helping organizations to develop and implement data-driven strategies.
• Business Analyst: Students can work as business analysts, helping organizations to develop and implement business intelligence solutions.
• Head of Business Development: Students can work as heads of business development, leading teams and developing strategies to drive business growth.
• Data Scientist: Students can work as data scientists, developing and implementing machine learning and statistical models to drive business insights.
• Data Manager: Students can work as data managers, responsible for the development and implementation of data management strategies.
• Business Intelligence Engineer: Students can work as business intelligence engineers, developing and implementing business intelligence solutions.
• Data Engineer: Students can work as data engineers, responsible for the development and implementation of data engineering solutions.