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 BIG DATA MANAGEMENT
Code EBUS305
Coordinator Professor T Bektas
Operations and Supply Chain Management
T.Bektas@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2021-22 Level 6 FHEQ First Semester 15

Pre-requisites before taking this module (other modules and/or general educational/academic requirements):

ULMS151 ORGANISATIONS AND MANAGEMENT 

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 12

6

      6

12

36
Timetable (if known) 60 mins X 1 totaling 12
 
60 mins X 1 totaling 6
 
      60 mins X 1 totaling 6
 
 
Private Study 114
TOTAL HOURS 150

Assessment

EXAM Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
Assessment 2: Unseen Examination Assessment Type: Written Examination Duration: 2 hours Weighting: 60% Reassessment Opportunity: Yes Penalty for Late Submission: Standard Anonymous Asses  2 hours    60       
CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
Assessment 1: Report Assessment Type: Coursework Size: 2000 Words Weighting: 40% Reassessment Opportunity: Yes Penalty for Late Submission: Standard Anonymous Assessment: Yes  -2000 words    40       

Aims

Upon completion of this module, students will be able to:
1. Demonstrate an understanding of what Business Analytics and Big Data are and to assess its relevance to business environments;
2. Evaluate potential for use of Business Analytics and Big Data, tools and their potential to give positive insights into decision-making and business intelligence;
3. Understand potential for new business opportunities and business models for adopting Business Analytics techniques and Big Data initiatives, and evaluate challenges associated with their implementation.
4. Appreciate the legal and wider ethical issues involved in the gathering of personal information
5. Understand types of solutions and applications used for Business Analytics and Big Data Management.


Learning Outcomes

(LO1) Students will be able to understand what Business Analytics and Big Data are and to assess their relevance to business environments.

(LO2) Students will be able to evaluate potential for use of Business Analytics and Big Data tools and analyse their output to business areas, such as Marketing and Operations.

(LO3) Students will be able to apply new business opportunities and business models for adopting Business Analytics techniques and Big Data initiatives, and evaluate challenges associated with their implementation.

(LO4) Students will be able to appreciate the legal and wider ethical issues involved in the gathering and evaluate the use of personal information associated with Big Data, such as from social media applications and internet websites.

(LO5) Students will be able to apply some knowledge of systems and tools used for Business Analytics and Big Data Management.

(S1) Adaptability

(S2) Problem solving skills

(S3) Commercial awareness

(S4) Organisational skills

(S5) Communication skills

(S6) IT skills

(S7) International awareness

(S8) Lifelong learning skills

(S9) Ethical awareness


Teaching and Learning Strategies

Teaching Method - Online Asynchronous Learning Method
Description: One hour weekly lecture
Scheduled Directed Student Hours: 12
Attendance Recorded: No

Teaching Method - Synchronous Lecture
Scheduled Directed Student Hours: 12
Attendance Recorded: No

Teaching Method - Seminar
Description: seminars or demonstrations
Scheduled Directed Student Hours: 6
Attendance Recorded: Yes
Notes: Through instructor-led seminars or demonstrations, students will review business analytics solutions and applications. Seminars or demonstrations may include presentations by industry participants, usually from related systems applications or software development companies or organisations engaged in business analytics projects or developments.

Teaching Method: Group Study
Scheduled Student Hours: 6
Attendance Recorded: No

Self-Directed Learning Hours: 114
Description: Students will spend approximately 75% of their self-directed lea rning time on activity associated with lectures, and 25% on activity associated with seminars. Students will research library resources for their lectures, and access on-line resources and training materials for seminars.

Skills/Other Attributes Mapping

Skills / attributes: Adaptability
How this is developed: Seminars and guided reading
Mode of assessment (if applicable): Coursework

Skills / attributes: Problem solving skills
How this is developed: Lectures, seminars and guided reading
Mode of assessment (if applicable): Coursework and Examination

Skills / attributes: Commercial awareness
How this is developed: Lectures and seminars
Mode of assessment (if applicable): Coursework and Examination

Skills / attributes: Organisational skills
How this is developed: Lectures and seminars
Mode of assessment (if applicable): Coursework and Examination

Skills / attributes: Communication skills
How this is developed: Lec tures and seminars
Mode of assessment (if applicable): Coursework and Examination

Skills / attributes: IT skills
How this is developed: Seminars
Mode of assessment (if applicable): Coursework

Skills / attributes: International awareness
How this is developed: Lectures and guided reading
Mode of assessment (if applicable): Examination

Skills / attributes: Lifelong learning skills
How this is developed: Seminars
Mode of assessment (if applicable): Coursework

Skills / attributes: Ethical awareness
How this is developed: Lectures and guided reading
Mode of assessment (if applicable): Examination


Syllabus

 

This syllabus will include (but is not limited to) the following:
1. Big Data (what big data means for business),
2. Extracting values from big data (the evolution of data analytics),
3. Working with big data and data analytics,
4. Application of various techniques (e.g., categorising, detecting patterns, clustering) to business areas such as marketing and retail management,
5. Interpreting and implementing a data-driven solution.
6. Foundations of Business Analytics,
7. Techniques from descriptive (e.g., visualising and exploring data), predictive (forecasting, simulation and risk analysis) and prescriptive analytics (e.g., optimisation), focusing on the application, interpretation and implications of these solutions in practice.


Recommended Texts

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