Master's Degree in Data Analytics Intelligence
Bogotá, Colombia
Master degree
DURATION
4 semesters
LANGUAGES
Spanish
PACE
Full time
APPLICATION DEADLINE
19 Nov 2026
EARLIEST START DATE
TUITION FEES
STUDY FORMAT
Distance Learning
Key Summary
About: The Master's Degree in Data Analytics Intelligence (MIAD) at Universidad de los Andes trains professionals to turn data into strategic knowledge. The programme integrates advanced analytics, data management and leadership and develops skills in data governance, computational techniques, analytical modelling, ETL of structured and unstructured data, cloud and big data technologies, programming languages and analytics libraries, database and server management, and visualization to present model results.
Career Outcomes: Graduates can work as data scientist, data analyst, analytics manager in consulting, finance, healthcare or technology. They can also pursue roles in business intelligence, data engineering, academic research or analytics consultancy.
The Master's Degree in Data Analytics Intelligence (MIAD) trains professionals capable of transforming data into strategic knowledge, integrating advanced analytics, data management and leadership to drive decisions that generate organizational value.
Program description
The Master's in Data Analytics (MIAD) trains professionals capable of leveraging data to generate value in their organizations and support decision-making. It develops skills in data management and governance, the use of computational techniques and analytical models, and project management. It is designed for those seeking to lead analytics initiatives in any sector.
Graduate profile
The graduate will be able to:
- Identify opportunities to apply analytical intelligence to generate value within organizations.
- Apply formal methodologies to translate business problems into analytics projects.
- Extract, transform, and load data from structured and unstructured sources using technologies for handling large volumes of data and cloud computing.
- Make use of technological tools such as computational languages, libraries for Analytics, database management and servers.
- Analyze, synthesize, and effectively present the results of analytical models using visualization techniques.
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