DATA MANAGEMENT AND VISUALISATION
2018/2019, Semester 2
School of Computing (Information Systems & Analytics)
Modular Credits: 4
This module provides you with the conceptual understanding and practical experience in two critical activities in the business analytics chain - (1) the management of data and (2) the exploration/communication of data and analysis through visualisations and dashboards.
(1) The Management of Data
In this part of the course, you will understand how data can be managed by computer systems. You will learn how to analyse and model a business problem in terms of its data requirements, and create the necessary structures to store that data efficiently. You will also learn how to access, manage and query that (and other data) sources to fuel your analyses. To understand these data stores, we'll learn about both relational and non-relational databases, and data warehouses. Topics include: relational and non-relational databases, database management systems, database design (conceptual and logical modelling), SQL (basic and advanced queries).
(2) Exploration/Communication through Visualisations
In this part of the course, you will understand how visualisations can be used to explore and communicate data and analyses. You will learn what visualisations are, what makes them effective, principles for designing them, and techniques to visualise temporal, spatial, proportionate, multivariate and complex data for both analysis and communication. You'll also learn about dashboards, and how to effectively design dashboards with visualisations for business analytics problems. Topics include: data visualisations, visual perception theories, presentation and representation, frameworks for designing and evaluating visualisations, dashboard principles, data stories and narratives.
Tools and Technologies
Through the course, you will develop and practice your data management skills using MySQL and MongoDB, and your visualisation skills using Tableau. Instructions on how to obtain these will be provided near the start of the semester.
There will be a 2-hr lecture, and a 2-hr hands-on (lab) session each week.
This course is assessed through continuous assessments (including two assignments), and does NOT have a final exam. Most of the assessments will be performed individually or in pairs (no teamwork*). Details on these will be available nearer the start of the semester.
We will execute our course using Slack* (rather than IVLE). Invitations to the Slack group will be sent to enrolled students before the start of the semester.
* - to be confirmed
CS1010 Programming Methodology or its equivalent, and BT1101 Introduction to Business Analytics
Workload Components : A-B-C-D-E
A: no. of lecture hours per week
B: no. of tutorial hours per week
C: no. of lab hours per week
D: no. of hours for projects, assignments, fieldwork etc per week
E: no. of hours for preparatory work by a student per week