ULMS Electronic Module Catalogue
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title BUSINESS ANALYTICS AND DIGITAL TOOLS
Code MKIB216
Coordinator Mr Y Cheng
Strategy, IB and Entrepreneurship
Yuxi.Cheng@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2024-25 Level 5 FHEQ First Semester 15

Pre-requisites before taking this module (other modules and/or general educational/academic requirements):
MKIB115 PROFESSIONAL AND ACADEMIC SKILLS FOR MARKETING; MKIB116 PROFESSIONAL AND ACADEMIC SKILLS FOR INTERNATIONAL BUSINESS STUDENTS 

Modules for which this module is a pre-requisite:
 

Programme(s) (including Year of Study) to which this module is available on a required basis:
 

Programme(s) (including Year of Study) to which this module is available on an optional basis:
 

Teaching Schedule
  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours 24

 6

         30
Timetable (if known)              
Private Study 120
TOTAL HOURS 150

Assessment
EXAM Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
             
CONTINUOUS Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
Assessment 3: Bloomberg Market Concepts MOOC Assessment Type: Practical Assessment Duration/Size: complete the BMC test anytime during semester 1 (deadline to complete by week 12) Weighting: 10%   0    10       
Assessment 2: Individual Report Assessment Type: Coursework Size: 2000 words Weighting: 45% Reassessment Opportunity: Yes Penalty for Late Submission: Standard UoL penalty applies Anonymous A  0    45       
Assessment 1: Group Report Assessment Type: Coursework Size: 2000 words Weighting: 45% Reassessment Opportunity: Yes - Students who are required to resit this assessment component will have to wo  0    45       

Aims

The module has the following aims:
To introduce students to the fundamental concepts of Big Data.
To familiarise s tudents with the use of various data sources to address real-world business challenges.
To introduce students to the basics of Statistical Concepts.
To support students developing in-depth understanding of software used in the workplace (such as Bloomberg, Excel, Stata).
To equip students with knowledge and skills on how to gather and interpret a range of macro-economic and firm-level data.
To introduce students to Business Ethics in relation to data collection, analysis, and intrepretations.

Learning Outcomes

(LO1) Students will be able to effectively utilise Bloomberg Terminals, Excel and Stata software

(LO2) Students will be able to apply state-of-the-art quantitative methods of data collection and analysis

(LO3) Students will be able to critically evaluate macro-economic and firm level quantitative data

(LO4) Students will demonstrate an in depth understanding on the use of Big Data in the business sector

(LO5) Students will be able to recognize and comprehend how experts in the private sector, public sphere, and international bodies use data in problem-solving to tackle intricate business and societal issues

(S1) Numerate

(S2) IT literate

(S3) Commercial awareness

(S4) Team player

(S5) Ethical awareness

(S6) International awareness

Teaching and Learning Strategies

Teaching Method: Lecture
Scheduled Directed Student Hours: 24
Attendance Recorded: Yes

Teaching Method: Seminar
Description: Students will carry out a task related to their lecture. This task will typically involve a group activity.
Scheduled Directed Student Hours: 6
Attendance Recorded: Yes

Self-Directed Learning Hours: 120
Description: This will consist of preparation for seminars and work on coursework as well as the completion of MOOCs.

Skills/Other Attributes Mapping

Skills / attributes: Numeracy
How this is developed: Students will learn how to analyse data and identify trends within data collected from various databases during lectures on macro- and micro-economic data gathering and analysis.
Mode of assessment (if applicable): Bloomberg Market Concepts MOOC and Group/Individual Report

Skills / attributes: IT skills
How this is developed: Students will use various databases to gather macro and m icro-economic data during seminars.
Mode of assessment (if applicable): Bloomberg Market Concepts MOOC and Group/Individual Report

Skills / attributes: Commercial awareness
How this is developed: Lecture and seminar content will cover examples of specific firms and industries and current opportunities and threats that they are facing.
Mode of assessment (if applicable): Bloomberg Market Concepts MOOC and Group/Individual Report

Skills / attributes: Team player
How this is developed: Students will work within a group to complete one of the assessments for this module. Students will also work in seminar groups to complete allocated activities.
Mode of assessment (if applicable): Group Report

Skills / attributes: Ethically aware
How this is developed: Lectures and Seminars will highlight important key ethical considerations and students will have to demonstrate ethical awareness when collecting and analysing data in their assessments.
Mode of assessment (if applicable): Group Report and Individual Report

Skills / attributes: International awareness
How this is developed: Students will participate in the lecture and seminar on cross-cultural communication to better understand differences of business communication and how businesses operate in different countries. Lecture and seminar material will also include various opportunities and challenges that multinational firms currently face. Global societal issues will also be covered in the module.
Mode of assessment (if applicable): Bloomberg Market Concepts MOOC and Group/Individual Report

Syllabus
 

1. Fundamentals of Big Data and Statistical Concepts (regression analysis, descriptive statistics etc)
2. Collection of Macroeconomic and Firm Level Data
3. Introduction to Software and programming – topics under this theme will include:
• Use of Bloomberg for data collection
• Use of Excel for data analysis
• Use of Stata for data analysis
4. Introduction to Big Data – topics under this theme will include:
• Big Data in Focus: Mobile Phone Data and Social Footprint
• Gazing from Above: Insights from Satellite Imagery
• Big Data Deciphers: Measuring Risk and Uncertainty
• Beyond Numbers: Delving into Textual Content Analysis
• The Global Fabric: Dissecting the Global Supply Chain Network
• Big Data Insights: Inequality and Social Mobility
• Analyzing Institutional Distance and Economic Growth through Big Da ta
• Linking Economic Development with Institutional Alterations
5. Critical Analysis of macro-economic and firm level data and big data
6. Business Ethics and their impact on data collection, analysis and interpretation.

Recommended Texts
Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.