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Module Specifications

Archived Version 2023 - 2024

Module Title
Module Code
School

Online Module Resources

NFQ level 8 Credit Rating 5
Pre-requisite None
Co-requisite None
Compatibles None
Incompatibles None
Description

Analytics, together with innovating technologies, including big data, will be the foundation of new and better businesses. The analytical process starts with data, and future business leaders need to guarantee that the data flow for business analytics is efficient and secure. By developing skills and experience in the design and implementation of cloud-based databases and workflow, students will master some of the most used technologies for managing data analytics in organisations. To do so, students will be familiarised with some of the most current tools for database management (e.g. Apache Spark), cloud computing (e.g. AWS ecosystem), and version control (e.g. GitHub). Students will also learn about data security and how to avoid breaches of API keys and other relevant data.

Learning Outcomes

1. Have the ability to work within a Data Analytics team using cloud-based technologies.
2. Set up an efficient Data Analytics workflow while ensuring the security of the data.
3. Have the ability to explain and apply the key functions of version control applied to data analytics.
4. Critically review the existing workflow of an organisation and suggest improvements to increase its performance



Workload Full-time hours per semester
Type Hours Description
Workshop12No Description
Lecture24No Description
Online activity24Github Self directed learning
Assignment Completion40No Description
Independent Study25No Description
Total Workload: 125

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Data Analytics Workflow in Organisations
Analytics scrum teams and sprints; Agile analytics project; Tools for efficient team collabortion

Cloud Computing
Database and storage applications; Instances, containers, and serverless computing

Version Control
Git and GitHub/GitLab commands; Collaborative Data analytics project management

Workflow Security
API key management; Potential security breaches and weaknesses

Workflow Performance
Processing speed and power; Scalability and reliability

Assessment Breakdown
Continuous Assessment% Examination Weight%
Course Work Breakdown
TypeDescription% of totalAssessment Date
Reassessment Requirement
Resit arrangements are explained by the following categories;
1 = A resit is available for all components of the module
2 = No resit is available for 100% continuous assessment module
3 = No resit is available for the continuous assessment component
Unavailable
Indicative Reading List

  • Caffo, B., Peng, R. D., & Leek, R. H.: 2016, Critically review the existing workflow of an organisation and suggest improvements to increase its performance, Leanpub,
  • Siegel, E., Glaeser, E. L., Kozyrkov, C., & Davenport, T. H.: 2020, Strategic Analytics: The Insights You Need From Harvard Business Review, Harvard Business Review,
  • Lisdorf, A.: 2021, Cloud Computing Basics: A Non-Technical Introduction, Apress,
  • Tsitoara, M.: 2019, eginning Git and GitHub: A Comprehensive Guide to Version Control, Project Management, and Teamwork for the New Developer, Apress,
Other Resources

None
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