Why Study This Programme?

Data is the lifeblood of many industries and understanding how to process, analyse and visualise that data is a skill much sought after by employers. The Diploma in Data Analytics is aimed at people who want to learn these skills and advance their career prospects. It’s also great if you work with data and want to boost your knowledge of analytics tools and processes to improve your overall productivity.

Programme Overview

The Higher Diploma in Data Analytics* is a one-year (60 credit) Special Purpose Award (SPA) programme that is awarded at Level 8 on the National Framework of Qualifications.

*Subject to validation by QQI

Data analysis is the process of evaluating datasets using statistical tools to reveal information you can make decisions with. Data analytics essentially examines large datasets to uncover not easily recognisable patterns, correlations, and other insights.

We’ll start by looking at the principles of the Data Analysis process, and the types of data you’ll be working with. Then we’ll examine the business aspects of analytics, the stakeholders and the Key Performance Indicators they use for decision making.

We then take a hands-on approach to guiding you through the tools that Data Analysts use every day; Excel, R, Python and Tableau, and how to apply these to real-world datasets and examples.

Who Is This Programme For?

The Diploma in Data Analytics is a one-year (60 credit) Special Purpose Award (SPA) programme that is awarded at Level 8 on the National Framework of Qualifications.

This diploma provides comprehensive coverage of the key aspects of the Data Analytics industry. It aims to deliver an in-depth analysis of the core issues that parties typically encounter in Data Analytics.

This course is intended for anyone who wants to take the data analysis technologies in Excel and similar Analysis Tools beyond formulas and add more advanced capabilities such as dashboards, hierarchies, and relationships.

Course Content

  • Understanding Business Intelligence, Metrics, and KPIs
  • Data Sources, Relational Databases and SQL
  • The Data Analysis Process
  • Working with Time Series, Cross-Sectional and Panel Data
  • Identifying Trends and Patterns with Regression and Correlation
  • Data Analysis Functions in Excel
  • Processing and Cleaning Data in Excel with IF, VLOOKUP and Text Functions
  • Creating Pivot Tables, Pivot Charts and Advanced Visualisations in Excel
  • Data Processing, Visualisation and Publication using R Studio
  • Using Python Pandas for Analytics
  • Building and Publishing Dashboards with Tableau
  • Data Science and Machine Learning Algorithms

Programme Structure

This programme will be offered through both part-time and blended learning. Learners wishing to study part-time will be on campus 2 evenings per week and some Saturday workshops. Learners choosing to study the blended option will be studying online 3 evenings per week. The programme takes one academic year to complete.

Entry Requirements

To be considered for admission to this programme, applicants must hold a Primary Honours Degree (level 8) in a non cognate discipline from a recognised third level institution or equivalent qualification.

Candidates will ideally be able to demonstrate technical or mathematical problem solving skills as part of previous programme learning. Typically holders of more technical, numerate degrees are likely to gain a higher ranking in any order of merit in selection for the programme.

Recognition of Prior Learning (RPL)
Learners may also access this course on the basis of recognition of prior learning or by assessment of prior experiential learning/informal learning. The process is implemented within the relevant school, by the relevant Head of School/Department or nominee and is overseen by the Registrar. For this particular programme applicants will be considered on a case-by-case basis based on their educational record, work experience, their ability to demonstrate technical or mathematical problem solving skills and a capacity to successfully participate in the programme.

For applicants whose first language is not English, a B2+ in CEFRL (IELTS Academic score of 6.0, or equivalent), is needed.

How To Apply

Springboard Eligibility:

Full information on your eligibility for the scheme can be found directly on the springboard website. For those who commence the programme and are actively employed at the time of enrolment you will be liable for 10% of the course fee (€450). If you are unemployed your feel will be covered in full if you are deemed eligible for the scheme. Proof of unemployment is required.

Applicants should first ensure that they are registered with springboard+ and can then submit an application through the Springboard+ website a member of the Admissions team will be in contact with you within 1-2 working days to advise you on the next steps to enrolment.