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Curricular information is subject to change
(a). Explain and illustrate properties of traditional and big data management and processing systems (ACID, CAP, BASE).
(b). Compare and contrast relational, NoSQL and newSQL data management systems.
(c). Describe, distinguish, and use big data technologies for batch, stream, and graph processing.
(d). Develop (design and implement) NoSQL, batch, streaming and graph big data applications.
Indicative Module Content:
Introduction to Big Data (Characteristics and classifications)
Database Concepts, Architecture, Database Modelling and Design
The Relational Data Model, SQL, and Introduction to MySQL
Introduction to NoSQL Databases, MongoDB document NoSQL database
MapReduce Programming Model, Introduction to Apache Hadoop, HDFS
Distributed Data Processing using Apache Spark
Introduction to Graph processing and developing large graph applications using Spark's GraphX
Introduction to Data Streams and developing streaming applications using Spark's structured streaming API
Machine learning (supervised, unsupervised, recommendation) using Spark's MLlib API
Student Effort Type | Hours |
---|---|
Lectures | 24 |
Practical | 24 |
Autonomous Student Learning | 62 |
Total | 110 |
It is strongly recommended that students have an acceptable competency level in bash scripting and Python programming language.
Remediation Type | Remediation Timing |
---|---|
Repeat | Within Two Trimesters |
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
• Online automated feedback
solutions and feedback to weekly quizzes, and to projects
Name | Role |
---|---|
Mr Cormac Murray | Tutor |
Practical | Offering 1 | Week(s) - Autumn: All Weeks | Fri 14:00 - 15:50 |
Lecture | Offering 1 | Week(s) - 1, 2, 3, 4, 5, 6, 7, 9, 12 | Tues 11:00 - 12:50 |
Lecture | Offering 1 | Week(s) - 8, 10, 11 | Tues 11:00 - 12:50 |
Practical | Offering 1 | Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 | Thurs 12:00 - 13:50 |
Lecture | Offering 1 | Week(s) - 20, 21, 25, 31 | Tues 11:00 - 12:50 |
Lecture | Offering 1 | Week(s) - 22, 23, 24, 30, 32, 33 | Tues 11:00 - 12:50 |
Lecture | Offering 1 | Week(s) - 26, 29 | Tues 11:00 - 12:50 |
Practical | Offering 1 | Week(s) - 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 | Wed 11:00 - 12:50 |