Database Technologies for Business Analytics
| Module title | Database Technologies for Business Analytics |
|---|---|
| Module code | BEMM459 |
| Academic year | 2025/6 |
| Credits | 15 |
| Module staff | Professor Nav Mustafee (Convenor) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 10 |
| Number students taking module (anticipated) | 200 |
|---|
Module description
In this module you will learn the basics of database design and how to manage data. You will learn how to use Python to access, manipulate and store data. You will develop a theoretical understanding of relational databases (RDBMS) and NoSQL databases. You will gain practical experience of using Structured Query Language (SQL), using python libraries for data access and data storage.
Module aims - intentions of the module
This module aims to equip you with both the theoretical knowledge and the practical skills required to:
(a) Design and implement a relational database (Entity-Relationship diagrams, normalisation );
(b) Use Data Query Language with relational databases - data definition language (DDL), data manipulation language (DML) and structured query language (SQL);
(c) Design and implement a NoSQL (non-relational) database (Redis, MongoDB, Neo4j);
(d) Use Python libraries to access relational databases and NoSQL databases.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. P1: Demonstrate knowledge and understanding of fundamental, and domain-specific, analytics methods and tools.
- 2. P5: Create, manage, interrogate, interpret and visualise data from a wide range of different sources, types and including structured and unstructured forms.
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 3. P6: Critically analyse the use of data within a business context, identifying strengths and limitations
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 4. P14: Demonstrate technological and digital literacy: Our graduates are able to use technologies to source, process and communicate information.
Syllabus plan
The following content will be covered during the course:
- Introduction to relational and non-relational databases (theory)
- Designing and developing relational and non-relational databases
- Entity-relationship modelling and normalisation (relational databases).
- Introduction to database languages – Data Definition Language (DDL), Data Query Language (DQL), Data Manipulation Language (DML)
- Using Structured Query Language (SQL)
- Using Python Libraries for working with databases
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 20 | 130 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Scheduled learning and teaching activities | 20 | Labs |
| Guided independent study | 90 | Reading and preparation for lectures and labs |
| Guided independent study | 40 | Preparation of assessments |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Quizzes and exercises during labs | In class | 1-5 | Verbal in-class |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 50 | 50 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Group Assignment | 30 | 1000 words | 1-5 | Written |
| Individual Reflection | 20 | c. 1000 words | 1, 3, 4 | Written |
| Examination | 50 | 1 hour | 1-2, 5 | ELE / Written and verbal where required |
Details of re-assessment (where required by referral or deferral)
| Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
|---|---|---|---|
| Group Assignment | Group Assignment (1,000 words, 30%) | 1-5 | Referral/Deferral Period |
| Individual Reflection | Individual Reflection (c.1000 words, 20%) | 1, 3, 4 | Referral/Deferral period |
| Examination | Examination (1 hour, 50%) | 1-2, 5 | Referral/Deferral period |
Re-assessment notes
Re-assessment will be in nature to the original assessment, but the topic, data, and materials must be new.
Deferral – if you miss an assessment for certificated reasons judged acceptable by the Mitigation Committee, you will normally be either deferred in the assessment or an extension may be granted. The mark given for a reassessment taken as a result of deferral will not be capped and will be treated as it would be if it were your first attempt at the assessment.
Referral – if you have failed the module overall (i.e. a final overall module mark of less than 50%) you will be required to re-take some or all parts of the assessment. The final mark given for a module where re-assessment was taken as a result of referral will be capped at 50%.
Indicative learning resources - Basic reading
The following texts will be referred to throughout the course:
- Coronel, C. (2020). Database principles: fundamentals of design, implementation, and management /. Cengage.
- Sullivan, D. (2015). NoSQL for Mere Mortals. Addison-Wesley Professional
- Perkins, L., Redmond, E., & Wilson, J. (2018). Seven databases in Seven Weeks: A Guide to Modern Databases and the NoSQL Movement. 2nd Edition. Pragmatic Bookshelf.
- Badia, A. (2020). SQL for data science: data cleaning, wrangling and analytics with relational databases (1st ed. 2020.). Springer. https://doi.org/10.1007/978-3-030-57592-2
- Python code (Tutor’s GitHub repository)
Key words search
Relational Databases, NoSQL, Python, SQL
| Credit value | 15 |
|---|---|
| Module ECTS | 7.5 |
| Module pre-requisites | None. |
| Module co-requisites | None. |
| NQF level (module) | 7 |
| Available as distance learning? | No |
| Origin date | 09/01/2020 |
| Last revision date | 09/04/2025 |
