Databases for Large Data-sets - CMI3509

Assessment 1: Other

Formative feedback will be provided during module delivery as practical exercises are completed.

Other

Assessment 2: Other

One formative tutor assessed presentation will be used part way through the module.

Assessment 1: Portfolio

Research a number of current database management systems that cater for large datasets and are based on a variety of relational and non-relational modules and produce a portfolio of real-world case studies where particular database management systems would find an application.

Portfolio

Assessment 2: Portfolio

Implement case studies showing how current database management systems can be used to create and query databases for large datasets and produce a portfolio of these. Case studies can be the ones included in the first portfolio. This should also include a discussion of relevant professional issues.

<p>The data needs of modern enterprises and organisations require a more flexible approach to data management than that offered by traditional relational database management systems. With organizations increasingly looking to Big Data to provide valuable business insights, it has become clear that new approaches are required to handle these new data requirements. Primarily focusing on non-relational data models, this module introduces you to alternative approaches to modelling the data needs of an organization. It also provides you with an opportunity to use non-relational databases and database technologies to build robust and effective organizational information systems.</p>

School of Computing and Engineering

<p>https://library.hud.ac.uk/readinglists/CMI3509</p>

Computing and Information Systems

CMI3509 - Databases for Large Data-sets

Databases for Large Data-sets

Critically analyse and evaluate competing data models and database technologies.

Use a range of modelling techniques to produce effective designs for non-relational databases using an appropriate design language to implement a non-relational database.

Explain how issues that are faced when working professionally (e.g. Codes of Conduct, Codes of Ethics) relate to data and the data system engineering process.

Understand the most appropriate type of modelling technique to describe an aspect of a database system.

Critically analyse, synthesize and evaluate material on a variety of topics fundamental to the topic of data engineering.

Elicit and conceptualize stakeholders needs.