Module Title:Data Intensive Applications
Language of Instruction:English
Credits: 5
NFQ Level:8
Module Delivered In 1 programme(s)
Teaching & Learning Strategies: The course is taught by means of lectures and supervised practicals. The practical work consists of lab assignments and tutorials focusing on scalable datastores and data processing systems. The laboratory exercise topics (data models, data processing, analysis, etc) are designed to explore and analyse features of a variety of data intensive systems.
Module Aim: To develop the student’s knowledge of the design, operation and management of cloud and on-premises data storage and processing systems.
Learning Outcomes
On successful completion of this module the learner should be able to:
LO1 Organize and analyze data to discover patterns and tends.
LO2 Deploy and scale modern on-premises and cloud data stores and warehouses.
LO3 Evaluate and rationalize modern polyglot data architectures
Pre-requisite learning
Module Recommendations

This is prior learning (or a practical skill) that is recommended before enrolment in this module.

No recommendations listed
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements
This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed.
No requirements listed
 

Module Content & Assessment

Indicative Content
1. Data Management in the Cloud
DaaS, DBaaS, Cloud-based DBMS Services, Security, AWS, EMC, Azure
2. Data Warehousing
OLAP, dimensions, measures, roll-up/drill-down, dimension & fact tables, star schema, data warehouse, data mart, materialized view
3. Data Analytics
market basket analysis, classification, association rules, clustering, decision trees, regression, neural nets, genetic algorithms, big data, total data
4. Scalable Datastores
Unstructured data, polyglot persistence, NoSQL, graph, document-oriented, columnar, key-value, NewSQL, Hadoop, Spark
Assessment Breakdown%
Continuous Assessment40.00%
Practical60.00%
Continuous Assessment
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Other Class test or written assignment (e.g. problem sheets, literature surveys, etc) 1,2 15.00 Week 6
Other Class test or written assignment (e.g. problem sheets, literature surveys, etc) 2,3 25.00 Week 12
No Project
Practical
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Practical/Skills Evaluation Laboratory assignments to be completed on weeks 3, 6 and 10. 1,2,3 60.00 Week 10
No End of Module Formal Examination

ITCarlow reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Frequency Average Weekly Learner Workload
Lecture 12 Weeks per Stage 2.00
Laboratory 12 Weeks per Stage 2.00
Independent Learning Time 15 Weeks per Stage 5.13
Total Hours 125.00
 

Module Delivered In

Programme Code Programme Semester Delivery
CW_KCCIT_B Bachelor of Science (Honours) in Information Technology Management 8 Group Elective 1