Database Technologies for Business Analytics
| Module title | Database Technologies for Business Analytics |
|---|---|
| Module code | BEM2040 |
| Academic year | 2024/5 |
| Credits | 15 |
| Module staff | Dr Shirley Atkinson (Lecturer) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 10 |
| Number students taking module (anticipated) | 60 |
|---|
Module description
In this module you will learn the basics of database design and how to manage data. This will include basic modelling topics as well as data retrieval and manipulation. You will develop a theoretical understanding and practical experience of SQL and relational databases. You will learn the basics of accessing some of those databases through Python.
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.
(b) Use Structured Query Language (SQL), specifically, Data Query Language (DQL), Data Definition Language (DDL) and Data Manipulation Language (DML).
(c) Use Python libraries to access relational and non-relational databases.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. Demonstrate knowledge and understanding of fundamental, and domain-specific, analytics methods and tools;
- 2. 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. 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. 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
- The relational model
- Entity Relationship modelling -- conceptual design
- Entity Relationship modelling – logical design.
- Introduction to database languages: DQL, DDL, DML
- Integrity and normalisation.
- Using Python Libraries for working with databases
- Miscellaneous.
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 Activity | 10 | Lectures |
| Scheduled Learning and Teaching Activity | 10 | Labs |
| Guided Independent Study | 70 | Reading and preparation for lectures and labs |
| Guided Independent Study | 60 | 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 | 1-4 | Verbal in-class |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 60 | 40 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Assessed workshop | 60 | 3 workshops throughout term | 1-4 | Written digital feedback |
| Final Exam | 40 | 1.5 hours | 1, 2, 4 | Written digital feedback |
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 |
|---|---|---|---|
| Assessed workshop | Re-assessment Coursework 2500 words (60%) | 1-4 | Referral/deferral period |
| Exam | Exam 1.5 hours (40%) | 1, 2, 4 | Referral/deferral period |
Re-assessment notes
Deferral – if you have been deferred for any assessment you will be expected to submit the relevant assessment. The mark given for a re-assessment 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 40%) you will be expected to submit the relevant assessment. The mark given for a re-assessment taken as a result of referral will be capped at 40%.
Indicative learning resources - Basic reading
The main texts are:
- Coronel, C., Morris, S., Crockett, K., and Blewett, C. (2020). Database principles. Fundamentals of design, implementation and management. Cengage, third edition.
- Sullivan, D. (2015). NoSQL for mere mortals. Addison-Wesley Professional.
Indicative learning resources - Other resources
Software:
- Students will mainly use Microsoft SQL Server Express, Visual Studio Code, and Python.
| Credit value | 15 |
|---|---|
| Module ECTS | 7.5 |
| Module pre-requisites | Proof of achievement in statistics and python. |
| Module co-requisites | None |
| NQF level (module) | 5 |
| Available as distance learning? | No |
| Origin date | 06/01/2020 |
| Last revision date | 30/01/2024 |
