Topics may include:

Motivation and rationale for the module, including skills development and employability; Data security and ethics; Types of data in business and finance; The sources of data in business and finance e.g. open source, social media and subscribed databases. Bangor University and BBS databases in business and finance; Applications of data in business and finance; Techniques to download, manipulate and manage data, (potentially including, but not restricted to, the application of skills developed in the module ‘Business Analytics Coding’); Opportunities to apply your skills later in your degree and career.

Assessment Strategy

A report and an essay 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

• Apply appropriate tools and techniques to undertake manipulation and management of datasets in business and finance settings.

• Articulate examples of the different types of data encountered in business and finance.

• Evaluate the relative merits of different business and finance datasets while articulating issues of data security and ethics.

• Explain the sources and applications of different types of data, especially in business, banking and financial markets.

• Identify and apply alternative approaches to download business and finance data from commercial databases and from publicly available sources.