| Unit name | Introduction to Business Analytics |
|---|---|
| Unit code | MGRC10001 |
| Credit points | 20 |
| Level of study | C/4 |
| Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
| Unit director | Dr. Essien |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
None |
| Units you must take alongside this one (co-requisite units) |
All other mandatory units |
| Units you may not take alongside this one |
None |
| School/department | School of Management - Business School |
| Faculty | Faculty of Social Sciences and Law |
Why is this unit important?
This mandatory core first year TB1 (Teaching Block 1) unit introduces students to business analytics, their programme peers, and the knowledge and skills required to apply business analytics in practice. Students will learn what business analytics is - it’s language, ways of thinking and doing - and the essential technical and non-technical knowledge and skills required to solve business problems effectively using data.
How does this unit fit into your programme of study
The mathematical and statistical methods learned in this unit are required for subsequent mandatory and optional quantitative units, while the programming skills learned in this unit are required for subsequent core business analytics units. The non-technical key skills developed in this unit will also prepare students for collaboration- and teamwork-focused units in the programme.
An overview of content
The unit will introduce students to examples of business analytics being used effectively and responsibly (and irresponsibly) in modern organisations and the key concepts and tools required to deliver successful business analytics projects. The unit will cover the essential mathematical tools required to formulate and solve business analytics problems, and the essential programming skills required to prepare and analyse data to answer business questions.
How will students, personally, be different as a result of the unit
Students will advance in their understanding and use of the mathematical and computational tools required to design, implement, and interpret business analytics solutions and in the language required to promote and integrate business analytics within organisations. Students will become more proficient in the programming skills required to prepare and analyse data and in the analytical and communication skills required to use the information in data to answer business questions. Students will also develop in their ability to work effectively in a team and to collaborate in a competitive environment.
Learning Outcomes
On completion of this unit, students will be able to:
ILO1: Demonstrate an understanding of what business analytics is, how it benefits organisations, how it impacts sustainable development, and when and how it should be used.
ILO2: Demonstrate an understanding of the meaning and use of mathematical and statistical concepts which are essential for the successful application of business analytics.
ILO3: Prepare data for analysis and assess the quality of data based on how it was collected.
ILO4: Explore and communicate the information contained in data to answer business questions effectively.
ILO5: Work effectively in a team to perform data analytics in a competitive environment.
Students may learn through interactive lectures, data analysis tasks, and industry-relevant case studies and simulations.
Pre-recorded (asynchronous) lectures may be made interactive through online quizzes; while on-campus / online (synchronous) lectures will be made interactive though polls, Q&A sessions, and group discussion. Both types of interactive lectures aid learning through listening, reading, memorisation, thinking, and action. Interactive lectures provide students an opportunity to learn essential business analytics and mathematical & statistical knowledge, while pre-recorded walk-through and live coding lectures provide students an opportunity to learn the essential programming knowledge required to implement business analytics in practice.
Data analysis tasks provide students an opportunity to learn through practical application of their business analytics, mathematical & statistical, and programming knowledge to solve data analysis problems. Data analysis tasks may follow a project-based approach to learning where data analysis tasks are clearly positioned in business analytics projects and require students to integrate domain knowledge and practical considerations into their analysis.
Industry-relevant case studies emphasise context-specific learning and application of business analytics knowledge and skills. Case studies provide an opportunity for contextual application of essential mathematical and statistical knowledge and programming skills and enable students to relate abstract concepts and technical skills to the real world. Case studies provide students with opportunities to see business challenges and subsequent (business analytics) solutions and results, and to learn through collaborative application of their knowledge and skills.
Industry-relevant simulations emulate real-life situations experienced in professional settings and provide a synthetic practice environment where students can improve their knowledge, skills and attitude through teamwork and collaboration. Simulations provide students with an opportunity to put their knowledge and skills into practice in safe, risk-free and controlled environments emulating the undefined and unpredictable nature of reality. The collaborate and competitive nature of the simulations engage and motivate students and prepare them for employability.
Tasks which help you learn and prepare you for summative tasks (formative):
Students may complete regular practice questions and data analysis tasks, either individually or collectively, and answers and solutions would be made available to students for self-assessment. These tasks help students learn towards ILO1 – ILO4 and prepare students for their examination and individual coursework assignment tasks. Students may also review, discuss, and reflect on fully developed case studies designed for students to learn all the steps required to answer business questions effectively using data (ILO3 and ILO4), and formative feedback would be provided to prepare students for their individual coursework assignment task. Finally, group-based data analytics tasks may be completed to help students learn how to work effectively in a team (ILO5), and students would be given the opportunity to reflect on their experience to prepare themselves for the group-related assignment task.
Tasks which count towards your unit mark (summative):
Examination (40% of the overall unit mark): Students will demonstrate their knowledge and understanding of business analytics (ILO1) and essential mathematical and statistical methods (ILO2) through their responses to examination questions and tasks.
Individual Coursework (40% of the overall unit mark): Students will demonstrate their ability to prepare data for analysis (ILO3) and to explore and communicate the information contained in data (ILO4) through a written report documenting their approach to solving a business problem using data.
Individual Reflection (20% of the overall unit mark): Students will demonstrate their ability to work effectively in a team to perform data analytics (ILO5) through a critical reflection on a group-based data analytics task.
Note: For the Individual Reflection assignment task, students will be assessed on the quality of their reflection and not on their group’s performance on the data analytics task.
When assessment does not go to plan
The re-assessment weightings on this unit will not be the same as the original assessment. This means if you do not pass the unit overall, then you will be reassessed with a single piece of assessment weighted at 100%, covering all Learning Outcomes for the unit. Please note, if you passed some components but did not reach the overall unit pass mark, those passed components will be disregarded and not included in the reassessment mark. Your overall mark in the unit will then be solely based on the reassessment work done in the summer reassessment period.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. MGRC10001).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the University Workload statement relating to this unit for more information.
Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
