Module: Data Science & Databases

Latest Module Specifications

Current Academic Year 2025 - 2026

Module Title	Data Science & Databases
Module Code	CSC1005 (ITS: CA119)
Faculty	Engineering & Computing	School	Computing
NFQ level	8	Credit Rating	5

Description

This module provides an overview to data management aspects of Data Science. It provides students with an introduction to Databases. Students should learn how to design and create a database using the entity-relationship model, express queries in SQL, understand relational database theory and validation concepts such as normalisation and functional dependencies.

Learning Outcomes

1. To understand the relational model theory that underpins database design.
2. To translate an informal problem specification into a well-formed Entity-Relationship model and map this to an appropriate relational schema.
3. To demonstrate a proficiency in writing SQL expressions to query and alter the database.
4. To understand the advantages of applying normalisation theory to validate database schemas.
5. To be able to apply summarisation and cleaning techniques in database applications for data science.

*Type*	*Hours*	*Description*
Workload	Full time hours per semester
Lecture	24	No Description
Laboratory	24	No Description
Directed learning	2	Enf of Year Exam
Directed learning	1	Lab Exam
Independent Study	74	No Description
Total Workload: 125

Section Breakdown
CRN	21460	Part of Term	Semester 2
Coursework	20%	Examination Weight	80%
Grade Scale	40PASS	Pass Both Elements	N
Resit Category	RC1	Best Mark	N
Module Co-ordinator	Mark Roantree	Module Teacher

Type	Description	% of total	Assessment Date
Assessment Breakdown
In Class Test	SQL Lab Exam	20%	Week 8
Formal Examination	Final Examination	80%	End-of-Semester

Reassessment Requirement Type
Resit arrangements are explained by the following categories; RC1: A resit is available for both^* components of the module. RC2: No resit is available for a 100% coursework module. RC3: No resit is available for the coursework component where there is a coursework and summative examination element. ^* ‘Both’ is used in the context of the module having a coursework/summative examination split; where the module is 100% coursework, there will also be a resit of the assessment

Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

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

Database Environment
Overview: Architecture, Components & Functions, Data Models.

Relational Model
Schemas, constraints, violations.

Relational Algebra
Relational Algebra Operators

SQL
Programming in SQL

Data Integrity
Capturing and maintaining integrity in relational databases.

Entity-Relationship Modelling
Using the E-R model to capture system requirements and database deployment.

Functional Dependency
Understanding functional dependency theory and rules.

Normalisation
Applying functional dependencies to ensure normalised databases.

Data Preprocessing for Data Science
Summarisation, cleaning and transformation of data.

Indicative Reading List

Books:

Thomas Connolly & Carolyn Begg: 0, Database Systems: A Practical Approach to Design, Implementation and Management, Addison Wesley,

Articles:
None

Other Resources

None