DATA WAREHOUSING AND BIG DATA

BUS5WB

2017

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-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 ServerPrescribedLarsonMcGraw Hill
ReadingsThe Data Warehouse Toolkit: The Definitive Guide to Dimensional ModelingRecommendedKimball and RossWiley

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

Select to view your study options…

Start date between: and    Key dates

City Campus, 2017, 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, building a data warehousing and data integration30 01
Assignment, using a warehouse for reporting and data mining40 01, 02
Report, big data analytics solution30 02, 03