F20BD - Big Data Management

Zi Hau Chin
Drishty Sobnath
Muhammad Marwan Muhammad Fuad
Albert Georg Burger
Radu-Casian Mihailescu

Course leader(s):

Aims

Syllabus

1. Web of data (1.1 Open data, Linked Open data, 1.2 Five-star framework, 1.3 Knowledge graphs)

2. Semantic web technologies (2.1 RDF, 2.2 RDFS, SKOS, 2.3 OWL, 2.4 Serialisation: RDF/XML, Turtle, Trig, JSON-LD, RDF-a)

3. Ontology modelling (3.1 Class properties, 3.2 Property restrictions, 3.3 Reification, 3.4 Named graphs, 3.5 Reasoning, 3.6 Alignment, 3.7 Validation and Evaluation)

4. RDF storage (4.1 RDF triple stores, 4.2 SPARQL)

5. Big data and relational databases (5.1 Characteristics of big data, 5.2 ACID properties, 5.3 Distributed database systems, 5.4 CAP theorem)

6. NoSQL databases (6.1 BASE principles, 6.2 PACELEC theorem, 6.3 noSQL characteristics)

7. NoSQL techniques (7.1 Partitioning and replication, 7.2 Eventual consistency, 7.3 Consistent hashing, 7.4 Object versioning and vector clock, 7.5 Quorum and conflict resolution, 7.6 Merkel trees and anti-entropy, 7.7 Gossip protocol)

8. NoSQL data models (8.1 Key-value, 8.2 Document, 8.3 Wide-column, 8.4 Graph, 8.5 NewSQL)

9. Data Integration (9.1 Data warehousing, 9.2 Virtual data integration, 9.3 Semantic data integration, 9.4 Data Wrangling, 9.5 Data mashing)

Learning outcomes

By the end of the course, students should be able to do the following:

Further details

Curriculum explorer: Click here

SCQF Level: 10

Credits: 15