MSc in Big Data Management and Analytics

Program Overview

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MSc in Big Data Management and Analytics

Overview

The MSc in Big Data Management and Analytics is a 1-year postgraduate program designed to equip students with the necessary skills and analytic mind-set to pursue a career in the dynamic data analytics industry.

Course Details

Type

Postgraduate

Duration

1 Year Full-Time

Validated by

QQI

Mode

Full-Time

Campus

Dublin Main Campus

NFQ Level

9

Course Highlights

• Emerging discipline with huge job opportunities
• Develop highly sought-after skills
• Fully aligned with industry needs
• Access to innovative tools and technologies
• A dedicated experienced lecturing team

Intake Dates

• Dublin - Full-Time - September 2025

What our students say

I found the course to be both challenging and rewarding as it gave me the opportunity to acquire a valuable accreditation whilst enhancing my computer expertise. The modules on the course are extremely interesting and beneficial, knowledge of which will prove useful in the IT marketplace.

ANNE-GAELLE GUILCHER
MSc in Computing

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• MSc in Network and Information Security
• MSc in Cloud Computing
• Master of Science in Interactive Digital Media

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Modules

Big Data Analytics

This module aims to equip the learner with a range of most relevant topics that pertain to contemporary analysis practices, and are foundational to the emerging field of big data analytics.

Information Retrieval and Web Search

This module introduces the learner to the concepts of information retrieval (IR) and web search.

Concurrent and Parallel Programming

The future of microprocessor development is based around multiprocessor multicore architectures that will deliver the performance required for future application demands.

Cloud Computing

This module aims to introduce the learner to the concept of cloud computing and how it differs from the client server model of computation that is seen on the web today.

Big Data Management

This module aims to equip the learner with the skills to implement, from the batch to the speed layer, an end-to-end Big Data storage system using the most current technologies.

Data Mining Algorithms and Techniques

This module aims to give learners a thorough understanding of different data mining techniques, algorithms and tools necessary to infer information from large datasets.

Applied Data Science

This module aims to introduce the learner to the fundamental principles of data science and equips them with “data-analytic thinking” necessary for extracting useful knowledge and business value from the relevant datasets.

Research Methods

This module serves to significantly deepen the learner's research skills, both in relation to the module related assignments and later in the completion of a dissertation/dissertation by practice.

Timetables

Timetables will be made available closer to the starting date.

How to Apply

Entry Requirements

Candidates applying for this course should have a 2.2 Level 8 honours degree in Computing Science, or a 2.2 Higher Diploma in Computing or related discipline or international equivalent and/or relevant work experience.

English Language

Griffith College is accepting the online Duolingo English Test (DET) as valid proof of English proficiency.

Fees

Tuition Fees

• Irish/EU citizens, living in Ireland: EUR 7,900.00
• Irish/EU citizens, living abroad: Please refer to the Irish/EU Living Abroad Fees.
• International: Please refer to our Non-EU Tuition Fees section.

Flexible payment options

Students wishing to pay their fees monthly may avail of our direct debit scheme.

Progression

Academic Progression

On completion of the Level 9 MSc in Big Data Management and Analytics, students may progress onto a range of Level 10 Doctoral programmes on the National Qualifications Framework.

Career Progression

Through the MSc in Big Data Management and Analytics, you will have gained valuable professional experience, specialised in a key emerging field and developed many technical skills. There is a wide range of career options for our graduates including:

• Data Analytics
• Business Intelligence Analyst
• Big Data Solutions Lead Engineer
• Technical Product Manager
• Big Data Architect
• Data Analytics Consultant
• Video Analytics and Data Scientist
• Data Science Expert
• Multimedia Systems Developer
• IT Operations Manager

FAQs

Q1: What is the course duration?

The course duration is 1 year for full-time students and 2 years for part-time students.

Q2. What study modes are available?

The MSc in Big Data Management and Analytics course is available in both full-time and part-time study modes.

Q3. What are the main career opportunities for graduates of the programme?

Graduates of the programme can pursue careers in a wide range of industries, such as finance, healthcare, retail, and technology. Potential job roles include data analyst, data scientist, big data engineer, machine learning engineer, and business intelligence analyst, among others.

Q4. What are the fees for the programme?

The fees for the programme can be found on the Griffith College website. As fees may change over time or vary depending on factors like nationality or study mode, it is advisable to check the course page or contact the admissions office for the most up-to-date information.

Q5. What are the payment options?

Griffith College typically offers various payment options for tuition fees, such as payment in full, payment by instalments, or payment through a sponsor. It is recommended to contact the admissions office or the finance department for specific details regarding payment options

Q6. What services are available to learners on campus?

Griffith College offers a variety of services to support learners on campus, including access to computer labs, a library, study spaces, and Wi-Fi. Additionally, students have access to academic support services, career services, counselling services, and various clubs and societies to enhance their overall learning experience.

Program Outline

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MSc in Big Data Management and Analytics

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Degree Overview:

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Objectives:

• Equip students with the necessary skills and analytic mind-set to pursue a career in the dynamic data analytics industry.
• Build upon students' knowledge of computing science and create big data specialists.

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Program Description:

This specialist Level 9 MSc aims to provide students with the expertise and proficiency to thrive in the rapidly evolving field of big data. Spanning one year of full-time study, the program equips graduates with:

• Essential knowledge and skills for a career in Big Data Management and Analytics.
• Practical understanding of appropriate design and implementation strategies used in developing Big Data solutions.
• Advanced analytical skills to explore the range of contemporary practices in big data analysis.
This program boasts a 100% employment record, highlighting its effectiveness in preparing graduates for the demanding job market.

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Outline:

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Program Content:

• The program delves into various aspects of big data, covering topics such as big data analytics, information retrieval, web search, concurrent programming, cloud computing, data storage, data mining, applied data science, research methods, and project management.

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Structure:

• The program comprises eight modules in total, delivered over two semesters.
Each semester covers four modules, followed by a 12-week project in the form of a dissertation or dissertation by practice.

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Course Schedule:

• The program is offered on a full-time basis, with the available intake dates listed on the course page.

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Modules:

• Big Data Analytics: Explores foundational concepts and practical applications of big data analytics, covering data collection, statistical analysis, and problem-solving techniques.
• Concurrent and Parallel Programming: Empowers students to write efficient programs for multiprocessor and multicore architectures.
• Cloud Computing: Explores the fundamentals and applications of cloud computing, including different model types, virtualisation, and web application development.
• Applied Data Science: Introduces learners to data science principles and provides hands-on training in solving real-world problems using data analysis techniques.
• Research Methods: Develops skills in conducting research, including identifying methodologies, formulating research questions, and analyzing data.

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Assessment:

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Assessment Methods:

• The program utilizes a variety of assessment methods including:
• Examinations
• Assignments
• Presentations
However, general criteria often include:
• Critical thinking and analysis
• Effective communication and presentation
• Originality and creativity

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Teaching:

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Teaching Methods:

• The program utilizes a diverse range of teaching methods to cater to various learning styles, including:
• Lectures
• Seminars
• Workshops
• Tutorials
• Project supervision

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Faculty:

• The program is delivered by experienced and qualified lecturers with expertise in big data, data analytics, and related areas.

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Unique Approaches:

• The program adopts a hands-on, project-based approach, allowing students to apply theoretical knowledge to real-world scenarios.
• The program emphasizes the use of industry-standard tools and technologies, ensuring graduates are well-equipped for the workforce.

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Careers:

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Career Paths:

• Upon completion of the program, graduates are prepared for various careers in the data analytics field, such as:
• Data Analyst
• Business Intelligence Analyst
• Big Data Solutions Lead Engineer
• Technical Product Manager
• Big Data Architect
• Data Analytics Consultant
• Video Analytics and Data Scientist
• Data Science Expert
• Multimedia Systems Developer
• IT Operations Manager

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Opportunities:

• Graduates can find employment in a diverse range of sectors, including:
• Finance
• Healthcare
• Retail
• Technology
• Government
• Research and Development

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Outcomes:

• The program boasts a high graduate employment rate, with many securing positions in leading companies across various industries.

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Other:

• The program is accredited by QQI, ensuring its quality and recognition both nationally and internationally.
• Students have access to a dedicated careers service to assist with job search and career development.
• The program offers flexible payment options to support students financially.
• Griffith College is known for its modern facilities, supportive learning environment, and vibrant student community.

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Irish/EU citizens, living in Ireland Study Mode: Full-Time Dublin: EUR 7,750.00 Irish/EU citizens, living abroad International Non-EU students: a Student Services and Administration fee of EUR200 is payable each academic year in addition to the fees quoted below. An Academic Administration Fee of €250 is payable each September at the start of term. For students starting in the January/February term, €125 is payable in February, and then €250 will be payable each September from then onwards. A 2% Learner Protection Charge is applicable each academic year in addition to the fees quoted. The fees above relate to Year 1 fees only. Flexible payment options Sponsorship Post: Student Fees, Griffith College Dublin, South Circular Road, Dublin 8 Email: accounts@griffith.ie 2% Learner Protection Charge All QQI accredited programmes of education and training of 3 months or longer duration are covered by arrangements under section 65 (4) of the Qualifications and Quality Assurance (Education and Training) Act 2012 whereby, in the event of the provider ceasing to provide the programme for any reason, enrolled learners may transfer to a similar programme at another provider, or, in the event that this is not practicable, the fees most recently paid will be refunded. QQI Award Fee Please note that a QQI Award Fee applies in the final year of all QQI courses.