BUS5WB
DATA WAREHOUSING AND BIG DATA
BUS5WB
2016
Credit points: 15
Subject outline
Modern organisations accumulate steadily increasing quantities of data in both structured and unstructured form. A data warehouse is fundamental to manage structured data while large-scale processing and storage technologies are required for the unstructured data. This unit focuses on the knowledge and skills necessary to conceptualise, design and develop such solutions. Students will start with the development of an actual data warehouse. They will use this warehouse to build cubes, design and execute multidimensional and tabular queries, generate reports and conduct data mining activities. The second half of the unit will focus on Big Data technology. Starting with an in-depth understanding of the Apache Hadoop stack and supporting technologies, they will run analytics algorithms on a live Hadoop instance to derive insights from unstructured data, analyse the outcomes and integrate with output from the data warehouse. Upon completion of the unit, students will possess the expertise necessary to build data warehouses and address real world Big Data problems.
SchoolLa Trobe Business School
Credit points15
Subject Co-ordinatorKok-Leong Ong
Available to Study Abroad StudentsNo
Subject year levelYear Level 5 - Masters
Exchange StudentsNo
Subject particulars
Subject rules
Prerequisites N/A
Co-requisites BUS5PB
Incompatible subjects N/A
Equivalent subjects N/A
Special conditions N/A
Learning resources
Readings
| Resource Type | Title | Resource Requirement | Author and Year | Publisher |
|---|---|---|---|---|
| Readings | Delivering Business Intelligence with Microsoft SQL Server | Prescribed | Larson | McGraw Hill |
| Readings | The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling | Recommended | Kimball and Ross | Wiley |
Graduate capabilities & intended learning outcomes
01. Build a data warehouse and demonstrate data integration capabilities from diverse data sources.
- Activities:
- Lectures and workshops
- Related graduate capabilities and elements:
- Inquiry and Analytical Skills(Creative Problem-solving,Inquiry/Research)
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
02. Develop a query strategy for online analytical processing (OLAP) and execute multidimensional and tabular queries that generate reports and lead to data mining activities.
- Activities:
- Lectures, workshops and assignments
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Writing)
- Inquiry and Analytical Skills(Creative Problem-solving,Inquiry/Research)
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
03. Understand the need for large-scale processing infrastructure in business analytics and execute analytics algorithms on such an instance to derive insights from unstructured data.
- Activities:
- Lecture and workshops
- Related graduate capabilities and elements:
- Literacies and Communication Skills(Writing)
- Inquiry and Analytical Skills(Creative Problem-solving,Inquiry/Research)
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
Subject options
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City Campus, 2016, Semester 1, Night
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Enrolment information
Subject Instance Co-ordinatorDaswin De Silva
Class requirements
Lecture/WorkshopWeek: 10 - 22
One 3.0 hours lecture/workshop per week on weekdays at night from week 10 to week 22 and delivered via face-to-face.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| Assignment, building a data warehousing and data integration | 30 | 01 | |
| Assignment, using a warehouse for reporting and data mining | 40 | 01, 02 | |
| Report, big data analytics solution | 30 | 02, 03 |