Data Management for the Big Data Age
Duration
- One Semester or equivalent
Contact hours
- 36 hours face to face + blended
On-campus unit delivery combines face-to-face and digital learning.
2023 teaching periods
Hawthorn Higher Ed. Semester 2 |
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Dates: Results: Last self enrolment: Census: Last withdraw without fail: |
Prerequisites
Concurrent Pre-requisite (can be completed prior to or same study period)
OR
Aims and objectives
This unit is designed to deliver a variety of technologies and techniques used in managing different types of data in the big data age. Database technologies including data modelling and database design at conceptual level, logical level and physical level, query language and processing, transaction management will be introduced. Two types of database systems – SQL and NoSQL will be presented and their differences will be discussed.
Unit Learning Outcomes (ULO)
On successful completion of this module the learner will be able to:
1. Explain features of big data and the roles of different types of data
2. Critically review the concepts and principles of databases and database management systems including relational data model for handling structured data
3. Use SQL to create, query and manipulate databases
4. Design databases using ER modelling techniques and functional dependencies using normalization
5. Select technologies for data storage and physical database design, query processing and transaction management
6. Use XML and JSON to design, query and manipulate semi-structured data and explain unstructured/text data processing and information retrieval techniques
7. Evaluate different types of NoSQL databases, their differences from SQL databases and big data technologies on MapReduce and Hadoop
Unit information in detail
- Teaching methods, assessment and content.
Teaching methods
Hawthorn
Type | Hours per week | Number of Weeks | Total |
Live Online Lecture | 2 | 12 | 24 |
On Campus Class (Computer Lab) | 1 | 12 | 12 |
Online Directed Online Learning | 2 | 12 | 24 |
Unspecified Activities, Independent Learning | 7.5 | 12 | 90 |
TOTAL | 150 hours |
Assessment
Types | Individual/Group Role | Weighting | Unit Learning Outcomes (ULOs) |
Assignment 1 | Individual | 15% | 3,4 |
Assignment 2 | Individual | 15% | 6,7 |
Tutorial Exercises | Individual | 20% | 1,2,3,4,5,6,7 |
Online Quiz | Individual | 50% | 1,2,3,4,5,6,7 |
Content
- 3Vs features of Big data and different types of data: structured, semi-structured and unstructured data
- Introduction to all database concepts
- Relational data model
- Entity Relationship (ER) models for database design
- SQL and SQL Programming Techniques
- Functional dependencies and normalization for relational databases
- Physical database design and query processing
- Transaction management - concurrency control and recovery
- XML related technologies and JSON
- Different types of NoSQL databases and their differences from SQL databases
- Big data technologies on MapReduce and Hadoop
- Unstructured/text data processing and information retrieval
Study resources
- Reading materials.
Reading materials
A list of reading materials and/or required texts will be made available in the Unit Outline.