Modules

Core Module Information
Module title: Data Analytics
SCQF level: 11:
SCQF credit value: 20.00
ECTS credit value: 10
Module code: SOE11154
Module leader: Ben Sebian
School The Business School
Subject area group: Management
Prerequisites

There are no pre-requisites for this module to be added
Description of module content:

The module aims at introducing you to the new possibilities opened up by the digital revolution and how these can be translated into the field of global logistics. You will be exposed to several data analytic techniques, including data cleaning, data visualisation, and dashboard report development (in R) with a focus on application to global logistics and sustainability. More specifically the module will cover aspects such as:(i) Introduction to Data Analytics: understanding the big data landscape; (ii) Data Processing; (iii) Data Visualisation: telling a story; (iv) Analytical Techniques: Introduction to Descriptive, Predictive, Prescriptive and Cognitive; (v) Simulation/Network Analysis; (vi) Practical Issues: Dashboard Development
Learning Outcomes for module:

Upon completion of this module you will be able to

LO1: Critically discuss relevant methods, tools, and techniques in data analytics in a business context.

LO2: Develop a critical understanding of the practical limitations of descriptive, predictive, prescriptive, and cognitive analytical techniques.

LO3: Apply practical skills for data analytics in R.

LO4: Critically reflect on the contribution of data analytics for different industry sectors.
Full Details of Teaching and Assessment
2024/5, Trimester 1, In Person,
VIEW FULL DETAILS
Occurrence: 001
Primary mode of delivery: In Person
Location of delivery: CRAIGLOCKHAR
Partner:
Member of staff responsible for delivering module: Ben Sebian
Module Organiser:


Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)NESH Description
Online Guided independent study 165 Direct reading. You will have to read materials about specific topics before you come in the class. You will use online materials (e.g., codes, articles, textbooks, videos, etc.) to understand in depth the content of the module. There will be short recorded videos of using computer language for analytical tools.
Face To Face Lecture 15 Lectures will present different theoretical concepts and models of data analytics connected with practicality. You will learn how to use analytical tools (e.g. descriptive, predictive analytics). In-class debate, quizzes and discussion: We will use different examples of data analytical tools and encourage you to participate in our discussion. This will help you to develop your critical thinking and skills.
Face To Face Practical classes and workshops 20 In workshops, you will use different databases and apply analytical techniques to understand how we can use different analytical tools. In this case, you will use analytical software in the computer labs and apply computer language for different analytical tools.
Total Study Hours200
Expected Total Study Hours for Module200


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words Description
Essay 50 1~2 Week 8 , WORDS= 2000 You will have to write an academic essay. The focus of the assignment will be to identify a problem within a relevant topic that a firm (or other user) may face and critically discuss how data analytics could be used to address this problem. You will have to connect the topic with different analytical tools.
Essay 30 2~4 Exam Period , WORDS= 1000 You will have to write an individual reflective essay on the creation of the application, noting what challenges you and your group faced, and how you overcame them.
Oral Presentation 20 3~4 Week 12 HOURS= 15 mins You will have to apply different analytical tools, do analyses with software and present the results of the analyses as a group presentation (15 min). You will be assessed for the quality of the application analysis (60%) and the delivery and analysis demonstration (40%). You will have to submit your presentation online and have a verbal presentation.
Component 1 subtotal: 50
Component 2 subtotal: 50
Module subtotal: 100

Indicative References and Reading List - URL:
SOE11154 Data Analytics
 

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