Overview

Introduction to data analytic infrastructure; Job types and roles in big data in business and finance; Privacy, ethics, security and encryption; Database frameworks / history of data storage in business/finance; Blockchains; Cloud based solutions and a survey of business/finance applications; Parallel computing and big data tools; Computing methods and different types of hardware; Algorithms, pseudocode and business processes; Emerging trends.

Topics may include: Introduction to data analytic infrastructure; Job types and roles in big data in business and finance; Privacy, ethics, security and encryption; Database frameworks / history of data storage in business/finance; Blockchains; Cloud based solutions and a survey of business/finance applications; Parallel computing and big data tools; Computing methods and different types of hardware; Algorithms, pseudocode and business processes; Emerging trends.

Assessment Strategy

A test and a report, based on different elements of the module content and learning outcomes.

Excellent: A- to A+ (70%+): Outstanding performance. The relevant information accurately deployed. Excellent grasp of theoretical/conceptual/practice elements. Good integration of theory/practice/information in pursuit of the assessed work's objectives. Strong evidence of the use of creative and reflective skills.

Good: B- to B+ (60-69%): Very good performance. Most of the relevant information accurately deployed. Good grasp of theoretical/conceptual/practical elements. Good integration of theory/practice/information in pursuit of the assessed work's objectives. Evidence of the use of creative and reflective skills. of the use of creative and reflective skills.

Satisfactory: C- to C+ (50-59%): Much of the relevant information and skills mostly accurately deployed. Adequate grasp of theoretical/conceptual/practical elements. Fair integration of theory/practice/information in the pursuit of the assessed work's objectives. Some evidence of the use of creative and reflective skills.

Threshold: D- to D+ (40-49%): No major omissions or inaccuracies in the deployment of information/skills. Some grasp of theoretical/conceptual/practical elements. Integration of theory/practice/information present intermittently in pursuit of the assessed work's objectives.

Learning Outcomes

• Articulate the security risks, particularly cybercrime, associated with a variety of deployment options for big data analytics in business and finance.

• Critically analyse the advantages and disadvantages of different deployment options for big data analytics in business and finance.

• Identify a variety of database and server deployment options for big data analytics and implement simple, prototype deployments for a business or finance application.

• Identify and evaluate frameworks for distributed storage and parallel processing using multiple (virtual) computers within a business and finance context.

• Identify the principles of cyber-safe deployment and implement basic safeguards to prototype deployments in a business or finance context.