Data Analytics

The Higher Diploma in Science in Data Analytics provides the practical knowledge and skills in the area of computing and data science for learners who wish to upskill or reskill in this area. The programme aims to develop learners' knowledge of the theory and practice of Data Analytics necessary for them to secure employment and perform as graduate level ICT /Data Analytical practitioners in a broad range of commercial, industrial and public sector environments.



Learners will benefit from theoretical knowledge fundamental to apply advanced analytics in web and business application, predictive modelling, statistics, programming, machine learning, and advanced visualisation to data sets through a variety of tools and techniques in order to generate actionable insights for stakeholders and support strategic decision making.



The objectives of the programme are to:

• Develop learner’s criticality in order to analyse industry trends in Big Data.

• Develop learners who are capable of performing robust, significant reports on the future orientation of the field of data analytics with specific emphasis on the problem domain.

• Provide learners with a platform to develop the requisite technical and design skills required by industry and to deepen knowledge of statistical analysis and analytical models.

• Enable learners to implement scalable Big Data applications.

• Prepare learners to work effectively and collaboratively in the execution of common goals.

• Provide work opportunities where learners can apply knowledge to a real-world situation.



This variety of learning approaches noted above can be offered including face-to-face, live online, recorded online, and directed e-learning. The experiential and practical nature of the programme is reflected in the most common learning approach in the program being lab-based lecturers and tutorials, together with classroom-based lecturers and tutorials.



Structure

The Higher Diploma in Science in Data Analytics is a one year full-time or two years part-time programme.



Semester one lays the groundwork for the programme and encompasses mostly foundational modules that focus on providing a solid and comprehensive understanding of the relevant concepts, a proficiency in the use of programming for data analytics and Statistics for Data Analytics and Databases and Business Application.



Semester two builds on this by covering advanced modules in which the knowledge, understanding and skills acquired in the first semester can be employed. Semester two also comprises an elective module of project or placement module, which focuses on applied skills.

The Higher Diploma in Science in Data Analytics has the following content:

• Statistics for Data Analytics

• Programming for Data Analytics

• Databases and Business Applications

• Platforms for Data Analytics

• Big Data Managing and Processing

• Data and Network Mining

• Applied Data Analytics

• Data Visualisation & Communications

• Advanced Analytics & Web Application

• Project

The minimum entry requirements for the Higher Diploma in Science in Data Analytics are:

• A Level 8 primary undergraduate honours degree with a minimum Pass classification from a recognised third level institution in a non-cognate area and ideally be able to demonstrate mathematical problem solving skills as part of previous programme learning. i.e. maths at Leaving Cert level would suffice.

Or



• A minimum Level 7 Ordinary Bachelor’s degree in a cognate area such as computer science,technology, networking, information systems, engineering, general science, mathematics, statistics, data science.

Or



• Applicants who do not have a Level 8 qualification and who have at least 3 years’ work experience may also be considered through the college’s normal RPL procedures. Relevant professional experience may be taken into account and inividuals will be assessed on a case - by-case basis through DBS RPL procedures.

We are now accepting applications for programmes taking place in 2025.

Teaching & Assessment


DBS teaching and learning strategies are intended to facilitate students to take ownership of, and responsibility for, their own learning in partnership with the academic faculty. A wide range of teaching and learning methods are used in the programme to ensure all learning styles are accommodated. Methods will include formal lectures, seminars, workshops, lab tutorials, on-line video demonstrations, and presentations that will emphasise student participation and application to case studies and relevant computing and business issues.


The focus of the programme is on the application of learning to the real-life environment and therefore a significant proportion of this programme is computer based. Learners will be required to practice taught skills and elements of the course via self-directed learning. Intellectual skills are developed through project work, tutorial work and coursework assignments.

ECTS Credits: 60

1 Academic year

Study Mode: Full-time



Delivery

For full-time students all learners are expected to attend in class in person.

For part-time students this programme is taught on a hybrid basis. This means learners are timetables either in-class or online, in a mix of online and in-class days.

Please email admissions@dbs.ie for course fees for the Higher Diploma in Science in Data Analytics.

Next Intake dates:

March 2025

September 2025

Career Opportunities

A number of Government Strategies and individual Expert Group on Future Skills Needs (EGSFN) reports states that the field of Data Analytics will generate 18,000 extra jobs between 2013-2020 in various ICT sectors including Software, Data Analytics, Financial Services, Distribution. Data Analysts are in strong demand from industry; those who are successful in completing the course are highly employable in fields as diverse as healthcare, finance and insurance, as well as cloud computing.



Roles types that may be suitable for graduates include:

• Senior Data Analyst

• Data Engineering and Analytics

• Financial Analyst

• Power BI Data Analyst

• Consulting: Data Analyst

• Lead Business Analyst