UFCFLR 15 M

UFCFLR-15-M Data Management Fundamentals

Overview

This module will introduce a range of fundamental and contemporary data management issues, techniques and tools that may be applied across the programme.

Objectives

1. Understand, evaluate and apply the relational model to structure data using a range of data query and manipulation languages and frameworks.
2. Design, develop and validate a range of data models and schemas incorporating a critical reflection on the value and ethical concerns of data.
3. Demonstrate competence with theoretical and practical aspects of enterprise data methods and strategies.

Curriculum

Topics are likely to include but are not limited to:

1) Relational modelling and key data management concepts

FAIR (Findable, Accessible, Interoperable) principles in data management CAP, BASE and ACID design principles Constructing and reverse-engineering entity relationship models Data normalisation Referential integrity and master data management Data processing models (batch, streaming, parallel)

2) Database construction

Forward engineering Keys, indexes and constraints

3) Data querying and manipulation

SQL basic (create, retrieve, update and delete) and advanced methods Query profiling and optimisation

4) Data cleansing and aggregation

Removing and refactoring Transforming and joining Anonymisation

5) NoSQL stores

Defining Difference to RDBMS Query and aggregation syntax

6) Architectures Data warehousing and batch operations (OLAP, OLTP, ETL) Data science pipelines Cloud and distributed data stores Partitioning and scaling

7) Data Management in Practice Environments Deployment Migration and integration Backup and recovery and disaster/breach mitigation

8) Security, Environmental and Ethical issues

Impact of data centres and mitigating climate footprint Data security and good governance Privacy

Assessment

Portfolio (100)