The aim of this module is to develop a deep understanding of Sport Intelligence (SI) information systems and their role in sports and business processes. SI is a discipline concerned with the transformation of data into meaningful and useful information for sports business analysis purposes. SI technologies are capable of providing interpretation of large amounts of data to identify and develop strategic business opportunities, based on insights that can provide a competitive market advantage and long-term stability. SI technologies also provide historical, current and predictive views of business operations. Common functions of business intelligence technologies are reporting and visualization, online analytical processing, analytics and data mining. These activities are designed to serve the business decision making process. This module builds on the students’ previous background and covers relevant topics such as data warehousing, data preparation and data visualization.
| Introduction to research methods | General introduction to research methods such as resources, literature reviews, document structure, referencing, etc. |
| Sport Intelligence | Introduction to Sports Intelligence, how sports intelligence adds value |
| Sports Intelligence Infrastructure | Understanding Sports Intelligence Infrastructure from data to knowledge |
| Sport Intelligence Applications | Understanding the decision making process |
| Sport Intelligence Process | Gathering Requirements Data Warehousing Dimensional Modelling ETL (Extract Transform Load) Data Reporting Services Data Visualisation |
| Front end | Querying and reporting, OLAP, dashboard |
| Data Mining | Data Mining methodologies Data Mining algorithms |
| Data privacy and ethics | General concerns and issues around areas such as data privacy law and regulations as well as ethical consideration of advanced data analysis |
Introduction to research methods
General introduction to research methods such as resources, literature reviews, document structure, referencing, etc.
Sport Intelligence
Introduction to Sports Intelligence, how sports intelligence adds value
Sports Intelligence Infrastructure
Understanding Sports Intelligence Infrastructure from data to knowledge
Sport Intelligence Applications
Understanding the decision making process
Sport Intelligence Process
Gathering RequirementsData WarehousingDimensional ModellingETL (Extract Transform Load) DataReporting ServicesData Visualisation
Front end
Querying and reporting, OLAP, dashboard
Data Mining
Data Mining methodologiesData Mining algorithms
Data privacy and ethics
General concerns and issues around areas such as data privacy law and regulations as well as ethical consideration of advanced data analysis
Methods used to achieve the module learning outcomes will include lectures, tutorials, laboratory practicals, interpretation of data, case studies, problem-solving exercises, video presentations, self-directed learning and computer-based learning
| Module Content & Assessment | |
|---|---|
| Assessment Breakdown | % |
| Other Assessment(s) | 100 |