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FIT 3182中等2 学分已补充 Handbook

Big data management and processing

莫纳什大学·Monash University·墨尔本
💪 压力
3 / 5
⭐ 含金量
4 / 5

📖 课程概览

Data engineering is about developing the software (and hardware) infrastructure to support data science. This unit introduces software tools and techniques for data engineering, but not hardware. It will cover an introduction to big data processing, covering volume, variety, and velocity; large volume data processing using parallel technologies; variety data formats, including unstructured and semi-structured data, using NoSQL databases; and velocity data processing, covering data streaming.

📋 Workload

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled teaching activities.

🎯 学习成果

Outcome 1

apply modern big data processing tools for various data structures;

Outcome 2

solve complex big data streaming problems.

Outcome 3

identify big data concepts and technologies;

Outcome 4

design and develop parallel database processing algorithms and methods;

Outcome 5

explain a variety of data formats in big data;

📝 考核构成

6 - Presentation

10%
LO: 5

Big Data Velocity Innovation

1 - Quiz / Test

40%
LO: 1, 2, 3, 4, 5

4 - Artefact

20%
LO: 2, 3, 4, 5

Big Data Volume, Variety and Velocity

3 - Demonstration

5%
LO: 2, 1

Big Data Volume Coding

2 - Artefact

15%
LO: 1, 2

Big Data Volume Coding

5 - Demonstration

10%
LO: 2, 3, 4, 5

Big Data Volume, Variety and Velocity

📋 课程信息

学分
2 Credit Points
含金量
4 / 5
压力指数
3 / 5
期中考试
2022年2月3日
期末考试
2022年2月3日

📅 开课方式

S1-01-MALAYSIA-ON-CAMPUS

Teaching Period
First semester
Location
Malaysia
Attendance
Teaching activities are on-campus (ON-CAMPUS)

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