DATA WAREHOUSING AND BIG DATA

BUS5WB

2018

Credit points: 15

Subject outline

Modern organisations accumulate increasing volumes of data in both structured and unstructured form.  A significant task in business analytics is to determine suitable information/data management solutions, architectures and platforms to suit business problem and context. In this subject you will focus on the knowledge and skills necessary to conceptualise, design and develop information/data management solutions. You will cover key topics in structured information management: relational modelling, SQL, dimensional modelling, data warehouse design and development, ETL, cubes, multidimensional and tabular queries, data mining on cubes.  You will examine Big Data technology. Microsoft Azure platform will be used to understand the Apache Hadoop stack, MapReduce and some IoT programming.  You will execute analytics algorithms on information management platforms to derive insights from unstructured data, analyse and integrate with output from the data warehouse. Upon successful completion of the subject, you will possess the expertise necessary to build data warehouses and address real world Big Data problems.


SchoolLa Trobe Business School

Credit points15

Subject Co-ordinatorDaswin De Silva

Available to Study Abroad StudentsNo

Subject year levelYear Level 5 - Masters

Exchange StudentsNo

Subject particulars

Subject rules

Prerequisites BUS5PB; or enrolled in HMSA or HGSA

Co-requisites CSE5DWD; or enrolled in HMSA or HGSA

Incompatible subjectsN/A

Equivalent subjectsN/A

Special conditionsN/A

Readings

Resource TypeTitleResource RequirementAuthor and YearPublisher
ReadingsDelivering Business Intelligence with Microsoft SQL ServerRecommendedLarson (2016)McGraw Hill
ReadingsThe Data Warehouse Toolkit: The Definitive Guide to Dimensional ModelingRecommendedKimball and Ross (2013)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
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
Inquiry and Analytical 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
Inquiry and Analytical Skills
Discipline -Specific Knowledge and Skills

Subject options

Select to view your study options…

Start date between: and    Key dates

City Campus, 2018, Semester 1, Night

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorDaswin De Silva

Class requirements

Lecture/Workshop Week: 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 elementComments% ILO*
Assignment 1: Dimensional design for an enterprise level business problemIndividual. Word equivalency: 230040 01
Assignment 2: Cube, OLAP and report developmentIndividual. Word equivalency: 210030 01, 02
Assignment 3: Report on big data analytics architectures and/or applicationsIndividual. Word equivalency: 210030 02, 03