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
School: La Trobe Business School (Pre 2022)
Credit points: 15
Subject Co-ordinator: Daswin De Silva
Available to Study Abroad/Exchange Students: No
Subject year level: Year Level 5 - Masters
Available as Elective: No
Learning Activities: Lectures, workshops and assignments.
Capstone subject: No
Subject particulars
Subject rules
Prerequisites: BUS5PB AND BUS5DWR
Co-requisites: N/A
Incompatible subjects: N/A
Equivalent subjects: N/A
Quota Management Strategy: Merit based quota management
Quota-conditions or rules: By the order of application to subject coordinator.
Special conditions: N/A
Minimum credit point requirement: N/A
Assumed knowledge: N/A
Learning resources
Delivering Business Intelligence with Microsoft SQL Server
Resource Type: Book
Resource Requirement: Recommended
Author: Larson
Year: 2016
Edition/Volume: N/A
Publisher: McGraw Hill
ISBN: 978 007 175 9380
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling
Resource Type: Book
Resource Requirement: Recommended
Author: Kimball and Ross
Year: 2013
Edition/Volume: N/A
Publisher: Wiley
ISBN: 978 111 853 0801
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Career Ready
Career-focused: No
Work-based learning: No
Self sourced or Uni sourced: N/A
Entire subject or partial subject: N/A
Total hours/days required: N/A
Location of WBL activity (region): N/A
WBL addtional requirements: N/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
City Campus, 2020, Semester 1, Night
Overview
Online enrolment: Yes
Maximum enrolment size: 120
Subject Instance Co-ordinator: Daswin 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 |