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Course Outline Title: BUSINESS INTELLIGENCE AND DATA WAREHOUSING Code: ITECH7406 Faculty / Portfolio: Faculty of Science and Technology Program Level: AQF Level of Program 5 6 7 8 9 10 Level Introductory Intermediate Advanced Pre-requisites: (ITECH1104 and ITECH1006 and ITECH5402) Co-requisites: Nil Exclusions: Nil Credit Points: 15 ASCED Code: 029999 Learning Outcomes: This course introduces students to business intelligence and data warehousing techniques used to analyse enterprise data sets. Topics may include theories and principles of data warehousing, business intelligence basics, value of DW and BI, relationship between DW and BI, DW architecture, DW types, designs and characteristics, BI model development, BI tools and technologies, data modelling, metadata and source data, data conversion, migration and storage, data quality issues, data mining, data marts, and online analytical processing. Knowledge: K1. Investigate the scope and application of various technologies within a business intelligence system context. K2. Investigate the major approaches to the development of business intelligence and reporting systems. K3. Develop knowledge of the theories and principles of data warehousing. K4. Understand the potential benefits of data warehousing. K5. Understand the relationship between business intelligence and data warehousing. Skills: S1. Apply business intelligence techniques using an industry standard approach to explore, extract and analyse enterprise data sets. fdlGrades UO_ITECH7406_2014/27_2014-10-27 10:11:17 CRICOS Provider Number: 00103D Page: 1/3 Course Outline ITECH7406 BUSINESS INTELLIGENCE AND DATA WAREHOUSING S2. Use complex multi-dimensional databases. S3. Coordinate data warehouse design, architecture, sourcing, implementation and governance approaches to managing data repositories. Application of knowledge and skills: A1. Communicate and foster realistic expectations of the role of technology and business intelligence systems in management and decision support. A2. Adopt problem solving and decision making strategies to communicate solutions with key stakeholders for a variety of issues relating to data warehousing and business intelligence solutions. Values and Graduate Attributes: Values: V1. Value the need to work collaboratively and autonomously on business intelligence and data warehousing problems. V2. Appreciate the strategic importance of business intelligence data. Content: Topics may include: • • • • • • • • • • • • • • theories and principles of data warehousing (DW) business intelligence (BI) basics value of DW and BI relationship between DW and BI DW architecture DW types, designs and characteristics BI model development BI tools and technologies Data Modelling Data conversion, migration and storage Data quality issues Data Mining Data Marts online analytical processing (OLAP) Assessment: This course is delivered in the form of directed learning activities, lectures and labs/tutorials. Students are encouraged to work independently and in teams to complete tasks. Learning tasks will be comprised of written evaluations as well as practical problem based activities. Learning Outcomes Assessed fdlGrades UO_ITECH7406_2014/27_2014-10-27 10:11:17 Assessment Task CRICOS Provider Number: 00103D Assessment Type Weighting Page: 2/3 Course Outline ITECH7406 BUSINESS INTELLIGENCE AND DATA WAREHOUSING K1,K2,K3,K4;S1,S2,S3 Develop skills in the analysis Tutorials/Assignment(s) 30%-50% Examination(s)/Presentation(s) 50%-70% and practical application of content introduced K1,K2,K3,K4;S1,S2,S3 Participate in lectures and labs/tutorials, read and summarise theoretical and practical aspects of the course Adopted Reference Style: APA Presentation of Academic Work: FedUni General Guide to Referencing fdlGrades UO_ITECH7406_2014/27_2014-10-27 10:11:17 CRICOS Provider Number: 00103D Page: 3/3