Studying online (if an online offering is shown below)
There are now 2 possible online modes for units:
Units with modes Online timetabled and Online flexible are available for any student to self-enrol and study online.
Click on an offering mode for more details.
Unit Overview
- Description
Relational databases are the backbones of modern businesses in processing transactions and storing customer data. Most organisations usually deploy several relational databases for operational convenience. It is quite often necessary to integrate the information existing in different relational databases for planning and decision making. Data warehouses are built to facilitate planning and decision making in businesses integrating data from different relational databases. Online analytical processing (OLAP) is a technology that uses a data warehouse for answering aggregation queries often used in planning. While relational databases hold important transactional information of a business, the success of a business quite often depends on advanced planning and development of strategies based on customer behaviour. Data mining technologies are used for discovering such patterns and trends in data stored in relational databases. This unit introduces the key mechanisms in data warehousing and OLAP. It discusses logical and physical design of data warehouses including star schema, snowflake schema, data marts, partitioning and materialised views. Students study the use of data warehouses through a study of the OLAP technology including the multidimensional OLAP (MOLAP) and relational OLAP (ROLAP) architectures, OLAP operations and structured query language (SQL) support for OLAP.
- Credit
- 6 points
- Offering
(see Timetable) Availability Location Mode Semester 1 UWA (Perth) Face to face - Details for undergraduate courses
- Level 3 core unit in the Data Science; Computing and Data Science major sequences
- Level 3 elective
- Outcomes
Students are able to (1) understand that discovering and extracting knowledge from a massive amount of data is a key problem in many scientific and business disciplines; (2) demonstrate a thorough understanding of key data warehousing and online analytical processing technologies; and (3) apply key data warehousing concepts in designing solutions for business data analytics.
- Assessment
Indicative assessments in this unit are as follows: (1) two project assignment and (2) final examination. Further information is available in the unit outline.
Student may be offered supplementary assessment in this unit if they meet the eligibility criteria.
- Unit Coordinator(s)
- Dr Siwen Luo
- Unit rules
- Contact hours
- lectures: 2 hours per week
labs: 2 hours per week - Text
-
Han, J. and Kamber, M. Data Mining: Concepts and Techniques, 2nd edn: Elsevier/Morgan Kaufmann 2006
- The availability of units in Semester 1, 2, etc. was correct at the time of publication but may be subject to change.
- All students are responsible for identifying when they need assistance to improve their academic learning, research, English language and numeracy skills; seeking out the services and resources available to help them; and applying what they learn. Students are encouraged to register for free online support through GETSmart; to help themselves to the extensive range of resources on UWA's STUDYSmarter website; and to participate in WRITESmart and (ma+hs)Smart drop-ins and workshops.
- Visit the Essential Textbooks website to see if any textbooks are required for this Unit. The website is updated regularly so content may change. Students are recommended to purchase Essential Textbooks, but a limited number of copies of all Essential Textbooks are held in the Library in print, and as an ebook where possible. Recommended readings for the unit can be accessed in Unit Readings directly through the Learning Management System (LMS).
- Contact hours provide an indication of the type and extent of in-class activities this unit may contain. The total amount of student work (including contact hours, assessment time, and self-study) will approximate 150 hours per 6 credit points.
Face to face
Predominantly face-to-face. On campus attendance required to complete this unit. May have accompanying resources online.
Online flexible
100% Online Unit. NO campus face-to-face attendance is required to complete this unit. All study requirements are online only. Unit is asynchronous delivery, with NO requirement for students to participate online at specific times.
Online timetabled
100% Online Unit. NO campus face-to-face attendance is required to complete this unit. All study requirements are online only. Unit includes some synchronous components, with a requirement for students to participate online at specific times.
Online Restricted
Not available for self-enrolment. Students access this mode by contacting their student office through AskUWA. 100% Online Unit.
NO campus face-to-face attendance. All study and assessment requirements are online only. Unit includes some timetabled activities, with a requirement for students to participate online at specific times. In exceptional cases (noted in the Handbook) students may be required to participate in face-to-face laboratory classes when a return to UWA’s Crawley campus becomes possible in order to be awarded a final grade.
External
No attendance or regular contact is required, and all study requirements are completed either via correspondence and/or online submission.
Off-campus
Regular attendance is not required, but student attends the institution face to face on an agreed schedule for purposes of supervision and/or instruction.
Multi-mode
Multiple modes of delivery. Unit includes a mix of online and on-campus study requirements. On campus attendance for some activities is required to complete this unit.