module specification

AC4055 - Data Science, Research and Analysis (2024/25)

Module specification Module approved to run in 2024/25
Module title Data Science, Research and Analysis
Module level Certificate (04)
Credit rating for module 15
School Guildhall School of Business and Law
Total study hours 150
 
105 hours Guided independent study
36 hours Scheduled learning & teaching activities
9 hours Assessment Preparation / Delivery
Assessment components
Type Weighting Qualifying mark Description
Unseen Examination 100%   Exam - 1.5 hours
Running in 2024/25

(Please note that module timeslots are subject to change)
Period Campus Day Time Module Leader
Spring semester North Wednesday Morning
Spring semester North Thursday Afternoon

Module summary

The Data Science, Research and Analysis module provides a fundamental grounding of basic knowledge of data science and computer software to facilitate the collection, analysis and presentation of accounting data. The module prepares learners for the accounting & finance and related professions. This will be achieved through learning relevant academic and practical skills which will enable learners to succeed academically and develop key workplace research skills. It also provides skills to analyse data, interpret and communicate qualitative/quantitative results in the form of information. Furthermore, the module deals with the collection, analysis, interpretation and presentation of accounting and financial data through measuring changes and associations of variables.

This module also provides basic skills in gathering and understanding of financial and non-financial data/information to develop complete knowledge of the client business and the environment in which it operates. It develops students’ basic skills and understanding to help them prepare business plans and advise on the actions to implement these plans. The skills developed through the understanding of data science and researching to provide solutions of issues raised in the accounting and finance sectors.

Syllabus

Part-1

1. Data Science, Digital & Technology (big data and data analytics)
- Data science and Artificial Intelligence: current developments and challenges; adding value into businesses & organisations; the role of AI in data science.
- The use of technologies to visualise data clearly and effectively,
-  Data science: sources & types of data; accessing big data and presentation for business & organisations using scientific methods.

2. Data Analysis and Statistical Techniques (analysing and evaluating data using appropriate technologies and tools)
- Sampling methods; forecasting techniques; summarising and analysing data; spreadsheet.

3. Basic skills set for numeracy leading to the ability to deal with more abstract mathematical concepts.

Part-2

4. Research skills: identifying current issues in accounting; define the problem; identify gaps; critical analysis; the use of primary data; survey tools.

5. Research skills and conducting basic research in accounting & finance

- use of research skills related database

6. Ethical judgement to the use of data and data technology

Learning Outcomes LO 1 - 3

Balance of independent study and scheduled teaching activity

Lectures and Tutorials:

The module will consist of lectures to introduce new topics and themes relevant to the accounting, economics and other related courses. The seminar sessions will provide the opportunity to practice the content covered in the lecture with and without the use of a computer software. The practice will help the students to understand the applied aspects of each topic covered in the lecture, particularly the quantitative analysis relevant to the subject areas. Learning will be supported by a developed Weblearn site, which students will be required to access on a frequent basis to prepare for lectures and seminars.

Learning outcomes

On successful completion of this module, students will be able to:

LO1: Explain the use of data science and how information technology can be used to inform and implement organisation strategy,

LO2: Identify and analyse data using mathematical & statistical techniques embedded in information technology for planning, decision-making, performance evaluation and control.

LO3: Apply their understanding of data and business analytics to research current issues in accounting using digital technologies.

Bibliography

https://rl.talis.com/3/londonmet/lists/718DACBE-7751-4DCF-8895-A0FF668C4C83.html?lti1p3LaunchId=lti1p3_launch_65807964d89c03.93700755&existingResourceLinkId=false&lti1p3LinkType=resource_link-best_guess&resourceLinkSingleOption=true&login=1

Core Text:

Quinlan, C., Babin, B., Carr, J., Griffin, M. and Zikmu, W. (2019) Business Research Methods, Cengage Learning 2nd edition

Additional Texts:

Oakshott, L. (2020) Essential Quantitative Methods for Business, Management and Finance, 978-1137518552, Bloomsbury Publishing Plc, 7th edition.

Saunders, M. N. K., Lewis, P. and Thornhill, A. (2023) Research Methods for Business Students, Pearson 9th edition. ISBN-10: ‎1292402725; ISBN-13:‎ 978-1292402727

Swift, L. and Piff, S. (2014) Quantitative methods for business, management and finance, 978-1137376558, Basingstoke: Palgrave MacMillan, 4th edition

Other Texts:

Boddy, D. (2019) Management: Using Practice and Theory to Develop Skill Pearson Education, Limited 8 Edition PRINT ISBN 9781292271811; EBOOK ISBN
9781292271804

Cottrell, S. (2019) The Study Skills Handbook, London: Red Globe Press; Macmillan International

Periodicals:
• Financial times
• The Wall street Journal Europe

Websites:
http://www.accountingtoday.com
http://www.restore.ac.uk/srme/www/fac/soc/wie/research-new/srme/modules/videos/index.html
http://www.bbc.co.uk/learning/subjects/maths.shtml

Journals:
Journal of information systems
The Accounting Review
Issues in Accounting Education

Electronic Databases:
• Science Direct
• FAME (UK Companies)
Education Research Complete