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Students
Tuition Fee
Start Date
Medium of studying
On campus
Duration
1 years
Program Facts
Program Details
Degree
Masters
Major
Data Analysis | Data Analytics | Data Science
Area of study
Information and Communication Technologies | Mathematics and Statistics
Education type
On campus
Timing
Full time
Course Language
English
About Program

Program Overview


Data Analytics – MSc

Course Overview

Data Analytics is the process of examining vast quantities of data, often referred to as Big Data, in order to draw conclusions and insights about the information they contain. Some examples of Data Analytics applications include real-time fraud detection, complex competitive commercial analysis, website optimisation, intelligent air, road and other traffic management and consumer spending patterns.


Big Data presents three primary problems: there’s too much data to handle easily; the speed of data flowing in and out makes it difficult to analyse; and the range and type of data sources are too great to assimilate. With the right analytics and techniques, these big data can deliver hidden and unhidden insights, patterns and relationships from multiple sources using Data Analytics techniques. This programme will ensure that you will be able to understand the data context, apply appropriate techniques and utilise the most relevant tools to generate insights into such data.


The Expert Group on Future Skills Needs report identified Data Analytics as an area of skills deficit. Given the wide range of industries in which Data Analytics can be utilised, the demand for Data Analytics graduates continues to soar. According to IBM, this demand is to increase by 28% by the year 2020 (Forbes, 2017). The average salary for Data Analysts in the US is $69,949 (PwC, 2017), in Ireland, the average salary is €44,758 (indeed ie, 2017).


Entry Requirements

  • A Level 8 or equivalent honours degree in Business, Science or Engineering.
  • Minimum grade of 2.1 (60%), comprising of at least 30 ECTS credits in any combination of maths, computer science or engineering.
  • English Language: Equivalent of IELTS 6.0 and above.

Course Modules

Semester 1

  • Data Analytics (5 credits)
    • Data analytics is an area of increasing importance and interest to organisations. Data analytics techniques offer huge potential in the creation of new knowledge products and services in addition to the enhancement of existing products and services. This module addresses the application of data analytics techniques to real-world business problems and the preparation of data for such scenarios.
  • Interpretation of Data (5 credits)
    • This module will teach students the importance of data pre-processing and data exploration. Students will prepare data for analysis using a range of advanced data processing techniques and software tools.
  • Programming for Data Analytics (5 credits)
    • Students taking this module will acquire the computer programming skills necessary to analyse and manipulate data sets. This module will introduce key programming concepts using programming languages designed specifically for data analytics.
  • Relational Databases (5 credits)
    • This module provides the student with the skills in areas such as entity modelling, normalisation and database design. In addition, significant time will be devoted to utilising the SQL language to operationalise the output of the design process, manage data and manage security in a modern relational database management system.
  • Statistics for Data Analytics (5 credits)
    • This module will introduce students to the use and role of probability models and statistical inference in data analytics. Laboratory work will give the student experience in applying probability and statistical models to real-world data.

Semester 2

  • Advanced Analytics (5 credits)
    • This module will build on the content covered in the Data Analytics module, focusing on analytics techniques and how these can be applied to specific business problems. The purpose of this module is to expand the student’s understanding of techniques employed in data analytics by exposing them to authentic case studies of approaches that organisations have taken to implement solutions to real problems in the field or based on scenarios which have no obvious solutions.
  • Advanced Databases (10 credits)
    • Advanced Databases will build on the Relational Databases module from Semester 1 and give students the opportunity to acquire a thorough understanding of stored procedures in the context of an enterprise database environment. A database programming language will be taught and students will study the key language constructs such as variables, conditional structures, loops, in addition to other more advanced topics such as cursors, functions, and packages.
  • Data Visualisation (10 credits)
    • This module develops student skills in data visualisation by introducing various data visualisation techniques. Students will learn how to explain the insights obtained from large data sets using data visualization techniques.
  • Research Methods (5 credits)
    • This module aims to introduce students to the key concepts involved in research and to develop their understanding of the uses and relevance of the major methodologies employed. The material covered in this module will form the basis for the research dissertation element of the MSc in Data Analytics programme, with one of the key outcomes of this module being a valid and robust research proposal for research in the area of Data Analytics.

Semester 3

  • Applied Research Project (30 credits)
    • The project builds on the Research Methods module, where the research proposal will have been developed and submitted. The dissertation will consist of 20,000 words, excluding appendices. As the capstone component of the programme, this element will help integrate the curriculum content, and working in conjunction with an approved industry partner, deliver a significant body of work that will contribute to the body of knowledge in the field of data analytics.

Career Opportunities

  • Data Analyst
  • Data Scientist
  • Performance and Analytics Analyst
  • Data Operations Analyst
  • Financial Marker Analyst
  • Business Intelligence Analyst
  • Customer Insight Analyst

Further Study

Upon successful completion of this programme, graduates have the opportunity to complete Level 9/10 programmes here at TUS or elsewhere.


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Technological University of the Shannon (TUS)


Overview:

Technological University of the Shannon (TUS) is a multi-campus university in Ireland, offering a wide range of undergraduate and postgraduate programs across various disciplines. It is known for its focus on applied learning and innovation, fostering strong industry ties and providing excellent employment opportunities for its graduates.


Services Offered:

TUS provides a comprehensive range of services to its students, including:

    Admissions & Support:

    Admissions guidance, international student support, open days, student finance information, induction programs, and student support services.

    Campus Life:

    Accommodation options, career and employability services, chaplaincy and pastoral care, disability supports, learning support, student counselling, student health services, sports facilities, student union, clubs and societies.

    Faculty Areas:

    Business, Hospitality & Humanities, Engineering, Built Environment & Informatics, Sciences, Health & Technology, and Limerick School of Art & Design.

Student Life and Campus Experience:

TUS prioritizes a student-first approach, offering small class sizes and personalized attention. Students can expect a vibrant campus life with a range of clubs, societies, and sports activities. The university also provides comprehensive support services to ensure a positive and enriching student experience.


Key Reasons to Study There:

    Applied Learning & Innovation:

    TUS emphasizes practical skills and real-world application, preparing students for successful careers.

    Strong Industry Ties:

    The university has strong connections with industry partners, providing students with valuable internship and employment opportunities.

    Excellent Employment Opportunities:

    TUS graduates are highly sought after by employers, with a strong track record of successful career outcomes.

    Vibrant Campus Life:

    Students can enjoy a diverse and engaging campus experience with a range of clubs, societies, and sports activities.

    Comprehensive Support Services:

    TUS provides a wide range of support services to ensure students' academic and personal success.

Academic Programs:

TUS offers a wide range of academic programs, including:

    Undergraduate:

    Programs in various disciplines, including business, engineering, science, technology, art, and design.

    Postgraduate:

    Master's and PhD programs in specialized fields.

    Apprenticeships:

    Programs in various trades and technical fields.

    Flexible & Professional Learning:

    Programs designed for working professionals.

Other:

TUS is a QS 5 Star Rated University, recognized for its high-quality education and research. The university is also actively involved in research and development, with a focus on areas of national and global importance.

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