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INFO703 – Big Data and Analytics

Module code
Module title
Big Data and Analytics
To enable students to gain the practical knowledge and skills required to store, manage and analyse large amounts of data, using appropriate algorithms.
  • BI1601
  • BI1804
  • IT7000
NZQA Level
Level 7
NZQA Credits
Delivery method
  • Web-Supported
Learning hours
Total learning hours
Resources required
Learning Outcomes
1. Examine application architectures for big data and analytics

2. Examine and apply data modeling approaches for data mining techniques

3. Design a solution and extract business value from big data

4. Demonstrate an understanding of commonly used industry tools
- Introduction to big data
- Hardware and software evolution
- Data knowledge discovery
- Data mining algorithms
- Traditional solutions and scalability problems
- Advantages of big data for business
- Industry use cases

- Information management
- Query and parallel processing
- Distributed computing
- Distributed storage

- NoSQL databases

- Concurrency , scalability and data processing

- Polyglot persistence conceptual architecture

- Big data warehouse and Enterprise data warehouse

- Data modelling approaches

- Selecting analytical models

- Performance attributes

- Extracting business value from big data

- Data scientist
Teaching and Learning Strategy
Teaching methods will involve theoretical and practical classes which may include but not limited to lectures, class discussions, tutorials, case studies, simulations, computer laboratory work, group activities, face-to-face and online activities.
Assessment Criteria
In order to receive a passing grade, students must achieve a minimum 40% average over all supervised tests and achieve 50% overall for the module.

Learning and Teaching Resource
Wintec Learning Management Systems, Computer Laboratory
Required Textbooks
An extended reading list will be supplied by the tutor at commencement of the module. This will be updated annually.

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