This module will allow the learner to assimilate a relational database environment and extract data on single and multiple tables using SQL. In addition, the learner will manipulate data results using aggregate functions, grouping and sorting.

1. Evaluate the relational model and the relational integrity rules
2. Define, create, alter and delete tables and data.
3. Write SQL commands for data manipulation of single
4. Retrieve data from multiple tables
5. Implement Inner, Outer, Left and Right Joins
6. Apply Aggregate Functions, Groups, Sorting and Pattern Matching

This module presents a detailed examination and practice of the advanced usage and functionality of SQL and T-SQL in an enterprise database environment using a suitable relational database management system.

1. Write complex SQL and T-SQL queries to retrieve information to aid business decisions
2. Implement T- SQL functions to support the display of a resultant data set
3. Devise appropriate ways to store and index data
4. Formulate triggers, stored procedures
5. Import and Export data using multiple data formats

This module will allow the learner to appreciate and examine the differing database environments and develop a design framework for relational database development. This module provides a practical led approach to fully understand the database design process.

1. Give an appraisal of the RDBMS, NoSQL and OODBMS environments.
2. Design a theoretical framework for a relational database
3. Evaluate the relational model and application of integrity rules.
4. Apply the technique of normalisation
5. Implement a Relational Database Schema

This module will introduce the learners scripting . Learners will design and implement object oriented programs for use in the administration of server systems .

1. Create scripts implementing data structures as appropriate to the business use case
2. Create objects which implement object relationships with reference to efficient code.
3. Apply basic error handling and debugging techniques
4. Devise and write threaded systems
5. Evaluate and implement best practices for scripted programs.

This module is designed to teach the essential skills students need to make effective contributions and to have an immediate impact on the accomplishment of projects in which they are involved. Students will learn techniques required to plan, manage and control projects

1. Compare and contrast different approaches to project management.
2. Apply risk management techniques.
3. Appraise techniques used to estimate project cost and duration.
4. Prepare graphical representations to plan and control a project.
5. Compare and contrast team organisations and select a suitable organisation based on project characteristics.

This module will provide the student with a significant level of comprehension both of the theoretical concepts underpinning business intelligence for Big Data and also how to critically appraise the appropriateness for industry.

1. Critically discuss the notions of intelligence
2. Perform data schema design and critically appraise modelling techniques.
3. Describe and implement techniques that improve on query performance
4. Justify the selection of complex queries appropriate to investigation and intelligence gathering
5. Critically appraise the needs of a given business sector in the selection of the appropriate KPIs for application in data analytics
6. Reflect upon their personal professional practice demonstrating appropriate and effective communication and organisational skills in the development of an application as part of a team
7. Analyse complex problems resultant from the use of large-scale data sources for business analytics and defend appropriate approaches to solving the business problem
8. Apply research, information gathering, critical analysis, design and implementation techniques appropriately and effectively

This module will also introduce students to the lifecycle of a Data Science project from data capturing to data visualisations. The student will explore the tools and techniques available to capture and analyse data to allow them to create a data science solution to meet business requirements. The student will demonstrate fundamental design principles and techniques to create meaningful visualisations of quantitative and qualitative data to facilitate decision making.

1. Appraise data categories (nominal and ordinal) and how data can be processed to solve a real-world problem or answer a research question.
2. Critically appraise data analysis techniques available to ingest raw unstructured data, transform, clean and manipulate this data for further analysis.
3. Examine and justify the selection of a suitable data statistic technique for a given set of requirements.
4. Apply best practise for data gathering, data cleaning, and data formatting to a specific use case, hypothesis or research question.
5. Design and implement a data solution for a given set of requirements that meets the professional context of the students that includes data visualisation and reporting.
6. Apply data analysis & reporting techniques with an awareness of emerging trends in data science.
7. Analyse and reflect upon the design and implementation techniques utilised and present the findings of the data analysis and visualisation completed.

This module aims to give students operational experience of design and implementation of information systems . Students should also be exposed to a professional working environment with the objective of maximising their employability and future career prospects whilst providing employers with highly capable staff who can demonstrate and apply their technical skills to real-world situation .

Placement will typically be 3 months but must be a minimum of 8 weeks.

1. Have experience with the dynamic required to work as part of a team in the design and development of information systems and related projects in commercial industry.
2. Identify, explore and make informed judgements relating to the work tasks/project on which they work.
3. Prepare a log book of their daily activities reflecting on personal professional practices appropriate in an industry setting.
4. Prepare a report on the work undertaken during the placement.
5. Utilise reflective learning as part of their personal and professional practice
6. Apply research, information gathering, critical analysis, design and implementation techniques appropriately and effectively.
7. Communicate effectively in order to enhance the understanding and engagement of a professional audience