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Strategy and Culture in a Data and Analytics Environment (NFQ Level 9, 10 ECTS)
Talent and Assets Management (NFQ Level 9, 10 ECTS)
Driving Business Outcomes (NFQ Level 9, 10 ECTS)
All modules are 100% continuous assessment.
As you are not registered with us, you will need to upload proof you can enrol to this programme.
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Talent and Assets Management (NFQ Level 9, 10 ECTS)
Driving Business Outcomes (NFQ Level 9, 10 ECTS)
All modules are 100% continuous assessment.
€1,600 per module
This programme is relevant to all areas of the financial services sector, in particular international financial services, fund management and all areas of banking. Learners will be at managerial and leadership level or aspiring to a leadership role.
On successful completion of this programme, you will be able to:
Describe and explain the challenges and opportunities provided by integrating data and advanced analytics in the provision and management of financial services
Examine current practice pertaining to data and analytics in a financial services enterprise or unit and recommend enhancements in design and skills base to ensure the unit provides a competitive service
Analyse the impact of a data driven culture and the business drivers in facilitating effective use of data and analytics tools and processes in financial services
Identify the key features of and evaluate the procedures / new technologies within an organisation which assists and empowers its personnel / business units as they learn to use data and analytics in their everyday work
Communicate clearly (using appropriate media) to pertinent stakeholders the impact of data and analytics on financial services and products design and delivery
Critically reflect on your professional role and contribution to financial organisations in the context of the application of data and analytics technologies and systems in financial services (and related sectors) and the implications arising from such developments.
If you hold an Institute designation or a designation managed by the Institute CPD hours may be awarded on successful completion of this programme.
e-learning, live stream lectures and workshops
When you successfully complete this programme you will be awarded a Professional Diploma in Data and Analytics in Financial Services from UCD.
100% Continuous Assessment.
The pass mark is 40% in all modules in line with UCD academic policy.
Laura Finnegan- Programme Manager
February 2020
Thursday, 23 January 2020
The minimum entry requirements are;
a) An Honours degree (second class honours grade 2 award or higher) in a business or relevant cognate discipline or
b) An Honours degree (second class honours grade 2 award or higher) in a non-business (or relevant cognate) discipline plus three years’ experience in a relevant role in financial services or
c) Exceptionally, students without a third level qualification but with extensive and demonstrable relevant financial services experience may also be admitted to the programme on a case-by case basis.
You must be a current member of The Institute of Banking, or become a member, to register for this programme. Membership is currently €40 per calendar year.
The data and analytics environment
Business and technology trends in data and analytics. The business value of data and analytics today. Regulatory environment and considerations. Data and analytics leadership.
Building a data and analytics strategy
Aligning data and analytics with enterprise strategies. Vision setting. Strategic frameworks for data and analytics. Opportunity mapping. Use cases in leveraging data and analytics. Aligning enterprise goals through data and analytics.
The data and analytics mindset
Engaging the C-Suite. Analytical acumen. Learning and education for data and analytics. Building data-drive decision making across the enterprise. Data tools and visualisation. Managing day day to day - integrity, dictionaries and longevity.
Best Practices in Data Management
Data management best practice. Data foundations. Data architecture. Data democratisation. Harnessing and filtering big data (structured/unstructured) New and emerging pillars in data management and architecture.
Data and Analytics Architecture and Technologies
Data storage and distribution. Data translation and quality. Data virtualisation. Data integration. Data processing. Data streaming. Knowledge discovery tools. Business Intelligence (BI). Predictive analysis. Cognitive (e.g. deep learning).
Managing Risk - Data & Analytics
Data governance. Data quality. Data longevity. Managing bias in decision making. Evaluating risk in data and analytics. Risk mitigation - software, hardware, data, operations, people, customer, and brand.
Leveraging Data & Analytics – Skills, Methods and Tools
Building the data and analytics team. Data analytics operating model. Interpretation and problem solving. Tooling and workplace. Learning and education for data and analytics.
Driving Business Outcomes
The application of 360 degree data and analytics. Aligning business strategy with data and analytics. Driving data and analytics business results. Framing questions and problem statements. The importance and limitations of data and analytics.
Future developments in Data & Analytics
Technology trends in data and analytics. Technology strategies and how they impact data and analytics. The importance and limitations of data, analytics, and modern technologies.