Module Code :- BMG880
Module Title :- Data Analytics
Module Level :- 7
Credit Points :- 20
RATIONALE :- Organisations are being compelled to collect organise store and disseminate data in large volumes to support decision making in order to improve business operations and achieve competitive advantage. Data management and analytics technologies have become widely accessible and affordable to businesses which are increasingly adopting these technologies to create useful insights from big data Businesses now require managers accountants and auditors to become expert users of business analytics tools to create valuable insights from both financial and non-financial data.
BMG880 Data Analytics Assignment – UK
This module introduces students to the strategic role that business intelligence and analytics play in creating an enterprise-wide data set that can then be transformed into valuable insights to enhance strategic decision making The module also provides students with an opportunity to use statistical analysis tools and data visualisation features of analytics software to deliver reports with real time information to managers to facilitate faster decision making. The module also in corporates fundamental concepts of business performance management.
AIMS :-
The aim of this module is to provide students with the knowledge and practical skills for applying business intelligence and data analytics principles to support management decision making in a business context.The module also equips students with quantitative analysis and data visualisation skills to derive valuable insights from the data in a business context.The module adopts learn by doing approach to implement relevant features of a performance dashboard as part of the design and implementation of performance management system for a case organisation.
LEARNING OUTCOMES :-
Successful students will be able to:
1 Demonstrate in-depth knowledge and understanding of business intelligence and data analytics methods tools and technologies within a business context
2 Analyse business data using appropriate statistical techniques
3 Show competence in the use of business intelligence and analytics software
4 Design implement and evaluate an appropriate business analytics solution within the context of business performance management.
5 Interpret outputs from data analysis and communicate findings in a professional manner
CONTENT :-
Enhancing decision making by using business intelligence and analytics tools
Systems Analysis and Design Methods
Entity Relationship Modelling
Performance Management Systems
Business Reporting using performance dashboards
Data Visualisation and data presentation methods
Descriptive, Predictive and Prescriptive Analytics
Big Data Analytics
LEARNING AND TEACHING METHODS :-
Lectures will be used to provide students with a review of the main concepts and theories of business intelligence and analytics Topics will be introduced through lectures or learning materials and explored through a variety of directed learning activities Each lecture will have its own specific learning objectives such as to enable students to develop their own understanding of a particular aspect of business intelligence data analytics systems analysis and design entity relationship modelling performance dash boards and big data analytics. An interactive approach will be adopted in lectures which draw upon case examples to facilitate application of theory to real-life situations critically analysing and making recommendations for appropriate ways forward to enhance business decision making.
BMG880 Data Analytics Assignment – UK
Student learning is further consolidated to in workshops where practical activities are designed to support learn by doing and case scenarios are presented for further application and analysis of the knowledge gained through the lectures and independent study.
Students will be encouraged to use both directed and independent learning to read academic and professional articles to expand their knowledge of current issues in business intelligence and business analytics. The module will use blended learning approach to further enhance students learning.
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