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 |
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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): |
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
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60 mins X 1 totaling 6
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60 mins X 1 totaling 6
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Private Study | 114 | ||||||
TOTAL HOURS | 150 |
Assessment |
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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 |
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Upon completion of this module, students will be able to: |
Learning Outcomes |
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(LO1) Students will be able to understand what Business Analytics and Big Data are and to assess their relevance to business environments. |
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(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. |
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(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. |
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(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. |
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(LO5) Students will be able to apply some knowledge of systems and tools used for Business Analytics and Big Data Management. |
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(S1) Adaptability |
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(S2) Problem solving skills |
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(S3) Commercial awareness |
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(S4) Organisational skills |
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(S5) Communication skills |
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(S6) IT skills |
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(S7) International awareness |
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(S8) Lifelong learning skills |
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(S9) Ethical awareness |
Teaching and Learning Strategies |
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Teaching Method - Online Asynchronous Learning Method Teaching Method - Synchronous Lecture Teaching Method - Seminar Teaching Method: Group Study Self-Directed Learning Hours: 114 Skills/Other Attributes Mapping Skills / attributes: Adaptability Skills / attributes: Problem solving skills Skills / attributes: Commercial awareness Skills / attributes: Organisational skills Skills / attributes: Communication skills Skills / attributes: IT skills Skills / attributes: International awareness Skills / attributes: Lifelong learning skills Skills / attributes: Ethical awareness |
Syllabus |
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This syllabus will include (but is not limited to) the following: |
Recommended Texts |
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Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module. |