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University of Exeter Business School

Database Technologies for Business Analytics

Module titleDatabase Technologies for Business Analytics
Module codeBEM2040
Academic year2023/4
Module staff

Dr Shirley Atkinson (Lecturer)

Duration: Term123
Duration: Weeks


Number students taking module (anticipated)


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:

  • Design and implement a relational database;
  • Use Structured Query Language (SQL), specifically, Data Query Language (DQL), Data Definition Language (DDL) and Data Manipulation Language (DML);
  • 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 ActivitiesGuided independent studyPlacement / study abroad

Details of learning activities and teaching methods

CategoryHours of study timeDescription
Scheduled Learning and Teaching Activity10Lectures
Scheduled Learning and Teaching Activity10Labs
Guided Independent Study70Reading and preparation for lectures and labs
Guided Independent Study60Preparation of assessments

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Quizzes and exercises during labsIn class1-4 Verbal in-class

Summative assessment (% of credit)

CourseworkWritten examsPractical exams

Details of summative assessment

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
Coursework602500 words1-4Written digital feedback
Final Exam401.5 hours1, 2, 4Written digital feedback

Details of re-assessment (where required by referral or deferral)

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
CourseworkRe-assessment Coursework 2500 words (60%)1-4 August/September Reassessment Period
ExamExam 1.5 hours (40%)1, 2, 4August/September Reassessment Period

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


Students will mainly use Microsoft SQL Server Express, Visual Studio Code, and Python. .

Key words search

Relational Databases, Python, SQL

Credit value15
Module ECTS


Module pre-requisites

BEM1024 Statistics for Business OR BEE1025 Statistics for Business and Management OR BEE1022 Introduction to Statistics

BEM1025 Programming for Business Analytics

NQF level (module)


Available as distance learning?


Origin date


Last revision date