bus5wb data warehousing and big data
DATA WAREHOUSING AND BIG DATA
BUS5WB
2020
Credit points: 15
Subject outline
This subject focuses on the knowledge and skills necessary to conceptualise, design, develop, implement and use such technology platforms. Students will learn to design and develop an actual data warehouse on cloud computing infrastructure. They will use this warehouse to build cubes for OLAP, write SQL and MDX queries, apply machine learning algorithms, generate reports and dashboards to communicate actionable insights. Students will learn how to configure and use a cloud computing environment (based on Microsoft Azure) to develop a technology platform that encompasses computing, networking, security and data management components. They will execute analytics techniques and machine learning algorithms on a live Hadoop instance to derive insights from unstructured data. Upon completion of the subject, students will demonstrate practical knowledge and skills necessary to construct and evaluates modern technology platform that addresses Big Data complexities
SchoolLa Trobe Business School (Pre 2022)
Credit points15
Subject Co-ordinatorDaswin De Silva
Available to Study Abroad/Exchange StudentsNo
Subject year levelYear Level 5 - Masters
Available as ElectiveNo
Learning ActivitiesLectures, workshops and assignments.
Capstone subjectNo
Subject particulars
Subject rules
PrerequisitesBUS5PB AND BUS5DWR
Co-requisitesN/A
Incompatible subjectsN/A
Equivalent subjectsN/A
Quota Management StrategyMerit based quota management
Quota-conditions or rulesBy the order of application to subject coordinator.
Special conditionsN/A
Minimum credit point requirementN/A
Assumed knowledgeN/A
Learning resources
Delivering Business Intelligence with Microsoft SQL Server
Resource TypeBook
Resource RequirementRecommended
AuthorLarson
Year2016
Edition/VolumeN/A
PublisherMcGraw Hill
ISBN978 007 175 9380
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling
Resource TypeBook
Resource RequirementRecommended
AuthorKimball and Ross
Year2013
Edition/VolumeN/A
PublisherWiley
ISBN978 111 853 0801
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
Career Ready
Career-focusedNo
Work-based learningNo
Self sourced or Uni sourcedN/A
Entire subject or partial subjectN/A
Total hours/days requiredN/A
Location of WBL activity (region)N/A
WBL addtional requirementsN/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
Subject options
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City Campus, 2020, Semester 1, Night
Overview
Online enrolmentYes
Maximum enrolment size120
Subject Instance Co-ordinatorDaswin De Silva
Class requirements
Lecture/WorkshopWeek: 10 - 22
One 3.00 hours lecture/workshop per week on weekdays at night from week 10 to week 22 and delivered via face-to-face.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | ILO* |
|---|---|---|---|---|---|
Technology architecture design and critical evaluation Individual. Word equivalency: 21 00 | Assignment | Individual | No | 30 | SILO1, SILO2 |
Construct, use and synthesis data warehouse Individual. Word equivalency: 2300 | Assignment | Individual | No | 40 | SILO1, SILO2 |
Adapt, use and evaluate a cloud computing environment for machine learning and big data complexities Individual. Word equivalency: 2100 | Assignment | Individual | No | 30 | SILO1, SILO3 |