Big Data Analytics

Is this course for me?
Our Master of Science in Computing in Big Data Analytics is a one year, full-time or two year, part-time programme. It focuses on the processes involved in examining and interpreting large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information.

From banking and financial services to retail and healthcare, as well as life sciences, the opportunities in big data analytics are expanding all the time, and this course provides you with excellent qualifications to make the most of the ever increasing opportunities.

After all, your skills can provide competitive advantage for businesses including more effective marketing and increased revenue which is why more and more companies have moved into the field, harnessing talents such as yours to exploit the huge volumes of data now available.

The opportunities for successful graduates exist in companies running large database systems, as well as the payment card industry and financial services. Roles typically include becoming a data storage manager, data analyst or data scientist.

Key features
• Data Analytics are used across all parts of the economy.
• Demand for Data Analysts is growing dramatically
• Flexible part-time and full-time options
• Industry input into course design

Subjects taught

What will I study?

Semester 1
• Business Intelligence (M)
• Mathematics for
• Analytics (M)
• Big Data Architecture
• (M)

Semester 2
• Machine Learning (E)
• Big Data Analytics (M)
• Data Science (E)

Semester 3
• Dissertation (M)

(M) = Mandatory, (E) = Elective

Entry requirements

Minimum Entry Requirements
Level 8 Honours Degree in Computing, or equivalent, second class honours (2.2), or Higher Diploma in Computing (Conversion Course into Computing). Non computing applicants must have a minimum of 30 ECT credits in Computing or Computing related modules, or computer industry experience. If you do not have an honours degree but have relevant experience you may also be eligible to apply via Recognition of Prior Learning (RPL). Applicants may also attend a one week bridging course where necessary.

Application dates

Non-EU Application Deadline: 25th June 2021


1 year, full-time
2 years, part-time

Post Course Info

Follow-on Courses
Follow up programmes elsewhere include:
• Level 10 studies (Doctoral) at other institutions and universities at home and abroad.

Career Pathways
The main employers are:
• Companies with Large Database Systems
• Payment Card Industry
• Financial Services

Graduate Careers
Former graduates are employed in the following capacities:
• Data Scientist
• Data Storage Manager
• Data Analyst

More details
  • Qualification letters


  • Qualifications

    Degree - Masters (Level 9 NFQ)

  • Attendance type

    Full time,Part time,Daytime

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    Course provider