Registry
Module Specifications
Archived Version 2016 - 2017
| |||||||||||||||||||||||||||||||||||||
Description This module aims to develop an understanding of the management and structuring of large datasets. This module will develop an understanding of critical role of data quality and data governance. Techniques for data visualization, particularly of large datasets, will be investigated. | |||||||||||||||||||||||||||||||||||||
Learning Outcomes 1. Analyse the requirements of applications handling large datasets. 2. Demonstrate an ability to efficiently structure a large dataset. 3. Implement data quality measures. 4. Identify and implement appropriate data visualization techniques. | |||||||||||||||||||||||||||||||||||||
All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml |
|||||||||||||||||||||||||||||||||||||
Indicative Content and
Learning Activities Data CollectionVolume, Velocity, Variety and Veracity; Parsing structures and unstructured dataData ManagementOptimizing data management; queries and impact on data management; information lifecycle; mapping, transformation and pre-processing. Data Annotations and meta-dataData QualityAccuracy; Completeness; Relevance; Consistency across data sources; Reliability; AccessibilityData VisualisationWhat is data visualisation? Visualisation basics; Traditional forms of data visualization; Visualising multi-dimensional data; Visualising large datasets (geo-spatial data, temporal data); Interactive visualizationPlatforms for Data Visualisation | |||||||||||||||||||||||||||||||||||||
| |||||||||||||||||||||||||||||||||||||
Indicative Reading List | |||||||||||||||||||||||||||||||||||||
Other Resources None | |||||||||||||||||||||||||||||||||||||
Programme or List of Programmes | |||||||||||||||||||||||||||||||||||||
Archives: |
|