Master in Big Data Analytics

Program Overview

Universidad Europea de Madrid

Master’s Degree in Big Data Analytics

Overview

The Master’s Degree in Big Data Analytics is designed to prepare professionals capable of managing the entire life cycle of a big data project: from configuring the infrastructure to advanced data analysis, always with a focus on business value.

Why Study the Master’s Degree in Big Data Analytics?

• Innovative curriculum that covers the entire data lifecycle, including the design and implementation of the architectures that will support distributed data storage and processing.
• Work-friendly schedule with a weekend timetable, allowing students to work and attend classes.
• Prestigious faculty with experts from a range of sectors and companies, such as Deloitte, Cryptoeconomic, and Telefónica.
• Experiential learning with real cases from top multinationals and training as a global big data professional.
• Access to cutting-edge facilities with high-capacity data clusters using Apache Hadoop, Spark, and NoSQL tools.
• Exclusive content and certifications, including the possibility of obtaining Cloud Practitioner and Machine Learning Specialty certification from the AWS Academy.

Program Structure

• The program is structured around a curriculum that covers many areas, including data management, analysis, processing, and visualization.
• Students will learn in depth about the management, analysis, processing, and visualization of data.
• The program includes a broad understanding of several areas, such as data mining, machine learning, data visualization, data management, big data analytics, statistics, and probability.
• Students will work on real case studies thanks to the academic model based on experiential learning.
• The program includes masterclasses given by experts in big data working at some of the most prestigious companies in Spain.

Career Opportunities

• Data Scientist: Responsible for defining data analysis questions and processes to transform data into value for the business.
• Data Architect: Responsible for defining and deploying the necessary infrastructure for big data projects.
• Expert in Data Analysis and Machine Learning: Responsible for programming data processing and machine learning systems.

Admissions

• Start your admission process by calling or requesting information, and our advisors will contact you.
• Once you have been admitted, secure your place by paying the reservation fee.
• Submit the required documents to formalize your enrollment.

Academic Quality

• The University has an internal quality plan whose objective is to promote a culture of quality and continuous improvement.
• The University is committed to promoting the achievement of external recognitions and accreditations, both nationally and internationally.
• The University measures and analyzes results, simplifies management, and maintains a relationship with the external regulator.

Frequently Asked Questions

• What can I do after the Master’s in Big Data Analytics?
  • After studying the master in Big Data Analytics, you’ll have a profile that many companies are looking for today. Many of those who graduate from this program enjoy successful careers in a wide variety of industries in roles including Data Scientist, Data Architect, and Expert in Data Analysis and Machine Learning.
• Is big data analytics in-demand?
  • Yes. Professionals with experience in big data analytics are in high demand today. With the explosion of digital data generated by various sources such as social media, e-commerce, and the Internet of Things (IoT), organizations are looking for ways to extract valuable insights and make data-driven decisions.
• What does a master in Big Data involve?
  • Our master's degree in Big Data is structured around a curriculum in which you will learn in depth about data management, analysis, processing, and visualization. The program covers many areas, and you will get a broad understanding of several areas including data mining, machine learning, data visualization, data management, big data analytics, statistics, and probability.
• How long does it take to study an MSc in Big Data?
  • The master in Big Data Analytics at Universidad Europea takes 10 months to complete and is made up of 60 ECTS. As part of the program, you will work on real case studies thanks to our academic model which is based on experiential learning. In addition, you will attend masterclasses given by experts in big data working at some of the most prestigious companies in Spain.

Program Outline

Degree Overview:

The Master's in Big Data is a course that covers Big Data analytics. It is designed for engineers, statisticians, mathematicians, or data analysts with a vocation in the field of ICT, seeking to expand their knowledge in storage techniques and distributed information processing, as well as big data analytics and visualization.

Objectives:

• Learn to apply cutting-edge technologies in Data Science and Machine Learning.
• Become an expert in managing large volumes of data and infrastructures, machine learning, and the analysis of business management processes.
• Prepare for the AWS Certified Machine Learning Specialty during the module on data processing and machine learning.

Teaching:

• The program includes experiential learning through real cases from first-level multinationals.
• Students will participate in simulations and role plays.
• A main one with more than 25 homogeneous processing nodes and 2TB of ram memory.
• A secondary one formed by 4 server machines with high processing and memory capacities (multicore, +64GB per node).
• Both clusters have Apache Hadoop, HDFS, Apache Spark, and Hive or Impala noSQL database access languages/tools.
• Students will benefit from collaboration agreements between Universidad Europea and prestigious companies.
• Students will be able to develop their final Master's project on real projects proposed by these companies and receive help and advice from specialists in the sector.
• LinkedIn includes Big Data specialist in its top 10 most in-demand jobs, with more than 360,000 vacancies.
• In its Emerging Jobs 2020 report, LinkedIn calculates a figure for the annual growth of the most promising professions.
In the case of Data Scientists, the annual growth rate will be 47%.