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Master in Data Science for Business

Become an expert professional in big data, developing skills for the collection and statistical interpretation of data.
This master's degree aims at training you with knowledge in the modeling, interpretation, and incorporation of data for decision-making in an organization, through quantitative methods that help maximize results and the management of organizational changes.

Core

Start your career path with an online career and unleash your true potential

We adapt to your study time

We develop programs with different schedules so you can graduate at your own pace.

19 months

Basic Program

What you will learn

Big data interpretation

Help organizations harness their data and use it to identify new opportunities and achieve higher profits, smarter business moves, more efficient operations, and happier customers.

Information encoding

Show your talent in mastering encoded data ready to be entered and processed by analytical software, describing, associating, and classifying them to find regularities, characteristics, and patterns.

Database management

Excel by effectively organizing and managing large volumes of data -both structured and unstructured-, and developing systems and software tools for managing them with the aim of achieving more efficient operations in any organization.

Problem-solving

Interpret statistical data for problem-solving by defining priorities regarding the acquisition and development of data systems, and selecting mathematical and computational tools for the collection, extraction, storage, and handling of big data.

Academic Validity

Where you could work

Big Data Management

Supervise and efficiently analyze different data systems within an organization.

Professional Services

Become an expert in examining analytical data to solve complex problems.

Banking Institutions

Make predictions to find solutions to financial and customer problems before they have an impact.

Data Analysis Consultancy

Interpret data to set patterns and opportunity areas.

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