Introductory description

Industries store a large amount of data for their day-to-day operations. The data related to customers, employees and machines are all managed using a database management system (DBMS). The data can be organized and can be accessed at any point for operations management using DBMS. Beyond essential requirements of data storage, modern DBMS also need to address the needs of efficiency and information security, These put a high demand for robust data systems.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

Data model,
Three-tier architectures,
Entity-relationship model,
Conversion of binary relationships,
Sub-classing,
Weak entity sets,
Relational model,
Relational data model,
Relational algebra,
Multi- statements transaction,
System constraints,
Queries on multiple tables,
Normalization,
Normalization process,
3rd normal form,
Object-oriented Databases,
Distributed databases,
Client/server Systems,
Data warehouses,
Object-oriented databases,
Conceptual design,
Logical database design,
Physical database design,
Generalization and aggregation,
Data quality,
Data security,
SQL, NoSQL

Learning outcomes

By the end of the module, students should be able to:

• Recall the role of data management systems in managing organisational data and information. [CITP:2.1.1]
• Describe how to use database management systems to perform basic queries to synthesise information and present it concisely. [CITP:2.1.2]
• Apply different data sources, formats, and structures to extract data from different sources. [CITP:2.1.2]
• Describe how to use different database management systems to handle structured and unstructured data, the relevant legal, ethical, social and security standards to a database system solution. [AHEP:4-C6][CITP:2.1.5,2.1.13]
• Reflect the approaches to data processing, including data modelling and data-driven decision making such as reducing data redundancy. [AHEP:4-C3]

Indicative reading list

View reading list on Talis Aspire

Subject specific skills

Contributes to the occupational standard for Digital and Technology Solutions Professional (ST0119):
Extract data from a range of sources. For example, databases, web services, open data (S54)

In addition, the module will develop students in terms of the following skills and knowledge:

• Reporting techniques, including how to synthesise information and present concisely, as appropriate to the target audience.
• Understanding data formats, structures, architectures and data delivery methods including “unstructured” data.
• Understanding sources of data such as files, operational systems, databases, web services, open data, government data, news and social media.
• Knowing approaches to data processing and storage, database systems, data warehousing and online analytical processing, data-driven decision making and the good use of evidence and analytics in making choices and decisions.
• Being able to extract data from a range of sources. For example, databases, web services, open data.

Transferable skills

Team working, problem-solving, oral and written communication, critical thinking, information literacy.