Data Visualisation & Insights (using PowerBi)
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This module is subject to validation.
Course Overview
This is a 5-credit level 7 micro-credential module which will enable participants to develop the technical, critical thinking and communication skills required to explore and present data to deliver valued insights to a targeted audience within the context of a data analytics project lifecycle. It will include a focus on the use of modern Data Visualisation tools such as Power BI.
With a focus on modern Data Visualisation tools, including Power Bi, this module will enable the student to: Research, identify and evaluate the key insights required to deliver value for a targeted set of stakeholders related to a data analytics project. Devise, implement and critique appropriate data visualisation theory and techniques for data exploration and to communicate results and insights to stakeholders.
What makes this course different
Exciting New Skills through funded programme
Equip yourself with key skills necessary for decision-making and competitiveness in a data-driven world, through this funded, flexible industry focussed programme.
In-Demand Graduates
A skills shortage in data analytics has been highlighted by the Department of Enterprise, Trade and Employment, with big data analytics listed as a critical skill.
Understanding the Industry
Information and Communications Technology (ICT), in particular data-driven technology, is a constant and integral element of the world we inhabit and affect. Advances in technologies such as Artificial Intelligence, Robotics and the Internet of Things are transforming the way we live and work. They are radically affecting how business is done and the Fourth Industrial Revolution is set to dramatically change society.
The disruptive impact of such change on world labour markets has already been felt and is anticipated to grow in an increasingly data-driven future. Skilled ICT workers are the driver of new development and of economic growth, and access to highly-skilled, analytical and adaptive citizens capable of dealing with, and making sense of, the massive amount of available data, is becoming a key factor in the success of companies worldwide.
The past decade has seen increased recognition of the importance of numeracy and mathematical skills in the technology sector, and acknowledgement that the ability to generate, understand and analyse empirical data is crucial for technological advancement. We note that the OECD Skills Outlook 2017, in discussing the types of skills that give countries global advantage, pointed to the increasing need for numeracy and mathematical skills, particularly in technologically advanced industries.
Today, data is viewed as the new international currency and the data-driven global economy is regulated by this incredible but revolutionary change from data poor to data rich. This can be seen in the domination by numerous data-centric capital entities. In-depth research of the storage, analysis and use of big data is attracting interest, from giant private data-centric enterprises to smaller data-driven companies, major government organisations and academic institutions. Examples include data-centric projects in Google, Facebook, Amazon, and Alibaba, the global pulse project initiation by the United Nations and strong EU data legislation, GDPR, to regulate the use and analysis of personal data.
We are living in the age of big data, data analytics and data science. The growth of big data presents tremendous knowledge, insights and challenges that result in ingenious innovations and economic growth opportunities. The availability of the right data and the ethical considerations around its use clearly comes into play.
Data-driven technology is changing the way we communicate, learn, live, work, and entertain. Hence, it is essential that we as a society develop the capability to utilise and understand data, it benefits and its implications. This is a view that is reflected in the Strategic direction and goals set out by many government agencies.
Career Opportunities
Data Visualisation skills combined with participants domain specific knowledge/skill will enable them to add value to their organisation and/ or improve their employment advancement and mobility.
Course Delivery and Modules
The module will be delivered over 1 semester.
Weekly classes will be delivered in a live synchronous format, 1 evening per week, typically Mondays from 6pm to 9pm. Attendance/participation in live classes will be important to master the material. Live online classes will be support by additional asynchronous activity (videos/ resources and tasks) which participants complete in their own time over scheduled periods.
Education Progression
Depending on their previous educational path, graduates from this programme may be eligible to enrol on other Data Analytics courses at DkIT.
Certificate in Data Analytics
Certificate in Large Language Models and Agentic AI New course
MSc in Data Analytics
Fees and Funding
This is a PEACEPLUS-funded programme, delivered via the SECBA project. More details on fees to follow.
Entry requirements
Standard Entry Requirements
- Republic of Ireland Applicants Standard Minimum Entry Requirements
- Northern Ireland Applicants Standard Minimum Entry Requirements
Recognition of Prior Learning
Applicants who do not meet the standard academic entry requirements but have significant relevant experience (certified and/or experiential) may apply to access this programme via the Recognition of Prior Learning (RPL) route. Learn more about RPL at DkIT
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Disclaimer: All module titles are subject to change and for indicative purposes only. All courses are delivered subject to demand and timetables are subject to change. Elective Module options will only run subject to student numbers. The relevant Department will determine the viability of each elective module option proceeding depending on the number of students who choose that option. Students will be offered alternative elective modules on their programme should their preferred elective option not be proceeding. Award Options for Common Entry Programmes: The relevant Department will determine the viability of each award option proceeding depending on the number of students who choose either option. If the numbers for one of the Award options exceed available places, students for this option will be selected based on Academic Merit (highest grades).