Business Intelligence and Data Visualisation

• • Concept of business value from corporate data, the exploitation of information for advantage, types and sources of information value
  • Nature and value of business intelligence, the business intelligence environment, and how types of data processing can add value
  • Knowledge discovery, data mining, data warehousing
  • Business analytics, OLAP analysis, metadata
  • Data visualisation, visualisation techniques, dashboard
  • The relationship between corporate strategy, IS strategy and business intelligence strategy
  • BI links to enterprise systems, Customer Relationships Management, Supply Chain Management, Structured & unstructured data, content management systems
  • Privacy, ethical, legal issues associated with BI Implementation
  • BI, Decision Support Systems, Expert Systems and Executive Information Systems
  • Data modelling, star schemas
  • Using select and complementary BI/BA tools to provide insights in decision making scenarios

You must have successfully completed the following subject(s) before starting this subject:

one of

• SWI-INF10002-Database Analysis and Design
• SWI-INF20004 (Not currently available)

and one of

• SWI-INF20003-Requirements Analysis and Modelling
• SWI-INF20016-Big Data Management
• SWI-INF20010 (Not currently available)
• SWI-INF20011 (Not currently available)

Others

Students should have completed 150 Credit Points (12 units) including the prerequisites listed above.

Additional requirements

No additional requirements

This subject was previously known as Business Intelligence.

This subject covers issues relating to deriving intelligence from various data sources for decision making purposes. Students gather skills to drive improved decision making process for senior management based on understanding data. Students will know the importance of understanding the short and long term goals of the organisation and how these impact the decision making process. Student will use tools that enable data analysis, predictive analytics, data visualisation to assist in the delivery of delivering real-time actionable intelligence.

• Group (30-50%)
• Individual (20-30%)
• Individual (10-20%)
• Individual (20-30%)

Current study term: 29 Aug 21 to 28 Nov 21