Business Analytics

MQF Level 5


Business Analytics

October 2024
Module Type
ECTS Credits
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Module Description

This module covers the essential skill of data analytics which are crucial to manage organisations producing high quantities of data during their operations.

Various concepts and methodologies are delivered comprehensively in this module, enabling the participants to establish a more rigorous thinking methodology where all decisions are educated and backed by data-driven conclusions.

This module recognises the difficulty that managers might face when employing mathematical and business models. It helps managers understand the importance of data modelling tools and techniques.

The aim is to increase accuracy and precision in reports as well as equip people in business so as to employ a questioning mind and be selective in the extraction and application of data.

Entry Requirements

Candidates who apply for this course will possess:

• A related qualification at MQF Level 4


• Two ‘A’ Levels (MQF Level 4) or equivalent one of which should be related to Accounts, Business or Economics and a pass in English Language and Mathematics at MQF Level 3 (‘O’ Level or equivalent).

• Preference will be given to applicants having 1 year work experience related to the study programme.

In the case of students who do not possess all the formal required academic qualifications, then the Recognition of Prior Learning (RPL) process could be applied such that if evidence of equivalent learning is found then the applicant could still be accepted in the course.

Such RPL process will subject applicants to an interview held with a board of experts within the field, chosen specifically by IDEA Academy, so as to verify their experiences and prior learning.

Students whose first language is not English and do not possess an ‘O’ level pass in English Language will be required to demonstrate English language capability at IELTS level 6.0 or equivalent. 

Target Audience

  • Individuals seeking to advance their academic and professional knowledge in Accounting.
  • Individuals wanting to pursue a wide range of accounting, consulting, financial and managerial career paths.
  • Individuals wanting to enhance their ability to interpret, assess and communicate financial related data.

Module / Unit Instructions

The proposed structure comprises a blended approach promoting the building of a community of practice via lecturer-to-student and peer-to-peer learning.

The structure uses primarily two dimensions of teaching-learning modes:

Module Components Structure: · Face-to-face sessions: 18 hours · Online Learning Activities: 12 hours.

Face-to-face sessions include lectures, tutorials, discussions, presentations and workshop activities promoting peer-to-peer learning.

Online learning activities incorporate tutorials and asynchronous discussions.

These may consist of active interaction, participation and contributions in fora discussions, sharing resources and self-reflection exercises.

Learners also contribute to the building of the community of practice by providing feedback to their peers as critical friends, enhancing the learner’s critical engagement throughout the study period.

How you’ll be assessed

This module consists of two individual assessments , each carrying a weighting as below:

a) Assessment 1 carries 30% of total module mark achieved. b) Assessment 2 carries 70% of total module mark achieved.

The overall grade achieved for each module is calculated as the sum of: • 30% of the mark achieved for Assessment 1; and • 70% of the mark achieved for the Assessment 2.

Both Assessment 1 tasks and Assessment 2 tasks aim to provide the learner an opportunity to produce evidence of his/her competences aligned to the learning outcomes of each individual Module.

Assessment 1 and Assessment 2 may include in-class assignments and home-based written assignments using diverse assessment tools which may take the form of online and in-class discussions, examinations of 2-3 hours, case studies, reports, proposals, essays, and presentations.

For successful completion of a study module the student is required to achieve an overall pass mark of 50%


Module Intake Dates

October 2024

Learning Outcomes


At the end of the module/unit the learner will have acquired the responsibility and autonomy to:

  • Discuss the importance of data analytics for business.
  • Appropriately apply data analysis skills.
  • Analyse different data analysis techniques & methodologies.
  • Report the findings from data analysis to specialist and non-specialist audiences.


At the end of the module/unit the learner will have been exposed to the following:

  • Examine the fundamentals and importance of business analytics.
  • Discuss the data analysis plan and data gathering.
  • Compare and contrast Data analysis techniques & methodologies.
  • Discuss real world use cases of business analytics.

At the end of the module/unit the learner will have been exposed to the following indicative content:

  • Business Analytics in practice
  • The fundamentals and importance of data analytics
  • Big Data
  • Descriptive Statistics
  • Data visualisation and reporting


At the end of the module/unit the learner will have acquired the following skills:

  • Gather data-based case study and present it using data visualization and reporting techniques.
  • Apply appropriately various data analysis techniques and methodologies.
  • Judiciously apply report writing skills.
  • Thoroughly analyse quantitative research results and present them to the specialist and non-specialist audience.
  • Analyse tables and charts in the data visualization and reporting process.

Judgment Skills and Critical Abilities:

The learner will be able to:

  • Collect, analyse, and interpret data/information to support arguments, and to develop solutions and apply problem-solving related to business analytics.

Module-Specific Communication Skills:

The learner will be able to:

  • Communicate ideas, problems, and solutions effectively to both specialist and non-specialist audiences verbally or in writing (PowerPoint presentations, reports, etc.) using a range of techniques involving qualitative and quantitative information.
  • Participate in class/online discussions and in organised workshops.
  • Present ideas, work, and findings to peers, lecturers, and specialist and non-specialist audiences.
  • Contribute to team work as required.

Module-Specific Learner Skills: 

At the end of the module/unit the learner will be able to:

  • Undertake independent and self-directed study through primary and secondary research.

Module-Specific Digital Skills and Competences:

At the end of the module/unit, the learner will be able to:

  • Examine how data can be modified.
  • Navigate through the online learning platform to find assignments, discussion boards, literature, tutorials etc.
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