Module Information

Module Identifier
CS27020
Module Title
Modelling Persistent Data
Academic Year
2018/2019
Co-ordinator
Semester
Semester 1
Pre-Requisite
Reading List
External Examiners
  • Dr Dirk Sudholt (Senior Lecturer - University of Sheffield)
  • Dr Hong Wei (Associate Professor - University of Reading)
 
Other Staff

Course Delivery

Delivery Type Delivery length / details
Lecture 40 x 1 Hour Lectures
 

Assessment

Assessment Type Assessment length / details Proportion
Semester Exam 2 Hours   Exam Period Assessment  Written Exam  60%
Semester Assessment Term Assessment  Regular 10 minute quiz worksheets, administered online  10%
Semester Assessment Term Assessment  Software development coursework - Implement a multi-table relational database  30%
Supplementary Assessment Resit Assessment  Software development coursework - Implement a multi-table relational database  40%
Supplementary Assessment 2 Hours   Resit Assessment  Written Exam  60%

Learning Outcomes

On successful completion of this module students should be able to:

Design and validate a database from a given enterprise description, justifying design decisions.

Implement a database design and a range of complex queries using a relational database management system (RDBMS).

Access a database through an appropriate programmatic interface.

Explain and provide a rationale for relational, semi-structured and alternative data model concepts.

Explain key principles of database and information security.

Aims

This module will provide a theoretical background in modelling persistent data using both relational databases and NoSQL systems. It will also introduce key concepts in information security.

Brief description

This module develops the concepts of database design, and implementation and use. The emphasis is on relational and semi-structured (XML) systems, with NoSQL systems introduced. It covers practical topics concerned with modelling and effective use of the facilities provided by a modern Database Management System (DBMS). Theoretical topics include data modelling, placing particular emphasis on the data model, relational algebra and the realisation of the relational model in a DBMS.

Content

1. Database System Concepts
Review and persistence, outline history. The value of general models: relational; object oriented; semi-structured. Databases, DBMS and applications programs. DBMS as reuse.

2. Relational Modelling
Entities and relationships. Connection traps. The design of relations. Transformation of an E-R model into a relational schema. Use of UML.

3. The Relational Model
Domains, relations and tuples. Primary and foreign keys. Referential integrity. Relational algebra. Null values and the outer join. Data normalisation. Validating a design.

4. SQL and implementation
Introduction. Status. DDL statements. SELECT clauses. Constraints. Built-in functions. Queries and views. Nested SELECT. Stored procedures.

5. Additional relational integrity constraints
Table and database level constraints. Triggers. Use of stored procedures.

6. Transactions
Introduction to transactions. ACID properties. Rollback.

7. Integration with high level languages
DBMS connections and services. An example API. Application development. The data dictionary.

8. The semi-structured database model and XML
The model: outline; perceived advantages. The XML standard. XMLSchema and overview, comparison with SQL. XPath, XQuery and XSLT: syntax; power. XML databases: native databases; extensions to RDBMS.

9. Database and Information Security
Threats to database and information. Techniques to secure persistent data, such as cryptography, steganography, access control and hashing.

10. Not Only SQL (NoSQL)
NoSQL background. NoSQL paradigms – BigTable, Key-Value, Document, Graph/Triple -stores. Choosing which NoSQL system is appropriate. NoSQL and ACID consistency

11. The Java Persistence API
Introduction to and practical demonstration of the Java Persistence API.

Module Skills

Skills Type Skills details
Application of Number Database programming involves higher level mathematical concepts.
Communication Exam and report writing develop written communication skills.
Improving own Learning and Performance Independent learning is necessary to complete the online quizzes.
Information Technology Information and communications technology is intrinsic to Computer Science.
Personal Development and Career planning There is a substantial demand for database programmers.
Problem solving Problem solving is intrinsic to programming in general, and to database programming in particular.
Research skills In order to develop a database application, it is necessary to research user requirements and available technologies. Additionally an understanding of databases enhances all research skills, as research materials now all reside in databases.
Subject Specific Skills Application of data modelling tools and technologies.
Team work This module will require individual rather than team work.

Notes

This module is at CQFW Level 5