MQM2DTM-Data Management

Module Provider: Business Informatics, Systems and Accounting
Number of credits: 20 [10 ECTS credits]
Level:7
Terms in which taught: Summer & Autumn Terms
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2022/3

Module Convenor: Dr Stephen Gulliver
Email: s.r.gulliver@henley.ac.uk

Type of module:

Summary module description:

The way a business stores and processes data can significantly impact the organisation’s ability to undertake specific business functions, meet customer needs, interact with critical stakeholders, and/or make key decisions. Poor data management can directly result in inefficient processes, poor reputation, and low turnover and profitability. This module highlights the importance of data management, from management and enterprise perspectives, by considering information theory, data storage solutions, enterprise and systems architecture, traditional information systems use, and critical decision-making approaches; in order to support students’ understanding that data management is key to achieving business success.

Aims:

The aim of this module is to provide students with the skills to a) undertake an analytical investigation of organisational data and information, in order to consider the nature, utility, and quality of available data; b) appreciate and support, from a management perspective, the implementation of data quality rule sets and guidelines, in order to facilitate knowledge workers (e.g. database designers); c) identify and appreciate how data needs can support business strategy; d) highlight what data must to be acquired, managed, and processed in business - using examples from a range of large, complex, and real-time datasets; e) understand a range of IS platform choices, and consider the properties, benefits, and problems of specific solutions in context of business operation and decision making, f) appreciate the data management issue involved in obtaining an enterprise systems perspective; and g) appreciate how relevant data hierarchies and taxonomies are identified and used to manage information and knowledge management and management decision making.

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To satisfy this general aim, students will acquire relevant knowledge and skills concerning:

• Information theory - in order to i) appreciate the form and value of data by learning the difference between D/I/K/W categories, ii) appreciation of meaning and abstract of information value via consideration of the semiotic ladder (with consideration of digital representation), and iii) appreciate the relationship between data / information, form, and business value.


• Value of database Management – i) understanding the possible value of data management, ii) ways in which data can be stored, and iii) appreciating the link between form and value.


• Enterprise architecture – to i) appreciate links that exist between business strategy, business process, systems software, and data architecture, and ii) appreciated the interplay between strategy, information systems, and data management.


• Business-model and Competitive Forces Analysis – in order to i) allow clarity in the business model, and ii) highlight, in context of market forces, gaps in alignment between business and IS strategies, and problems in the provision of a profitable and attractive value proposition.Ìý


• Business use of Information System – by i) defining IS, and ii) showing how information systems have traditionally been used to capture, manage, and disseminated data, information, and knowledge in order to support organisational activities, and iii) how systems can integrate without alignment.


• Data Management Solutions – in order to i) appreciate a selection of available data management and information processing solutions, and ii) critically appreciate the benefits and compromises facing business management.


• Decision making - appreciating i) the value and complexity of timely and meaningful decision making, ii) considering how data management is impacted by the decision type, and iii) the limitations and issues related to current decision approaches.


• Consideration of metadata, data hierarchies, and/or use of taxonomies to support effective business information storage and retrieval.

Assessable learning outcomes:

On completion of this module, the student should be able to:

1. Discuss the nature of data, information, and knowledge in order to appreciate the relationships that exist between information form, information use, and business value.


2. Describe how business systems architecture and data quality impacts information analysis, transparency, and enterprise operation.


3. Consider, in context, how representation of data and storage format impacts business capability.


4. Appreciate the definition of Information Systems in order to appreciate how business data has traditionally been processed.


5. Critically analyse possible data storage solutions, and the compromises in use that impact business performance.


6. Appreciate some contextual factors impacting business decision making.


7. Discuss, in context of the work-based company, the relevant approaches to enterprise knowledge capture, representation, and effective management.

Additional outcomes:

• Become familiar with commonly used database structures.


• Become familiar with analytical approaches for assessing business system and performance.


• Become familiar with a range of IS solutions

Outline content:

The key themes of the module are:

1. Information Theory


2. Value of Database Management


3. Enterprise Architecture


4. Business-model and Competitive Forces Analysis


5. Business use of Information Systems


6. Data Management Solutions


7. Metadata, hierarchies, and Taxonomies


8. Data Management Solutions


9. Decision MakingÌý

Global context:

N/A

Brief description of teaching and learning methods:

This module will be taught in a blended learning approach, which mostly includes directed self-study, undirected self-study, and workshops. It assumes no prior knowledge or experience of information systems and/or data management, therefore students are expected to do a fair amount of wider reading. A range of ‘case examples’ and supporting material will be provided, via e-learning systems, to support individual students in self-study. Business analysis and recommendation plan wil l be worked on across themes, but needs to be focused, documented, and submitted as part of a report, which is worth 100% of their grade.

Contact hours:

Ìý	Autumn	Spring	Summer
Lectures			16
Seminars			9
Supervised time in studio/workshop			12
Work-based learning			36
Guided independent study:	Ìý	Ìý	Ìý
Ìý Ìý Wider reading (directed)			36
Ìý Ìý Exam revision/preparation			10
Ìý Ìý Preparation for tutorials			9
Ìý Ìý Preparation for performance			9
Ìý Ìý Essay preparation			55
Ìý Ìý Reflection			8
Ìý	Ìý	Ìý	Ìý
Total hours by term	0	0	200
Ìý	Ìý	Ìý	Ìý
Total hours for module	200

Summative Assessment Methods:

Method	Percentage
Written assignment including essay	100

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

Submission of an individual report (4000 word limit + appendices) analysing operation and information systems within the work-based company, with the aim of highlighting, and planning, how data management could support specific improvement in business performance.

Formative assessment methods:

Students will be given feedback on the progress of their individual project through tutorials and practical sessions. Online quizzes will be made available to help assess students’ understanding of the subject. These are for their own benefit and will be marked automatically. The grade of formative assessment will not contribute towards the overall module mark.Ìý

Penalties for late submission:

The below information applies to students on taught programmes except those on Postgraduate Flexible programmes. Penalties for late submission, and the associated procedures, which apply to Postgraduate Flexible programmes are specified in the policy £Penalties for late submission for Postgraduate Flexible programmes£, which can be found here: /cqsd/-/media/project/functions/cqsd/documents/cqsd-old-site-documents/penaltiesforlatesubmissionpgflexible.pdf
The Support Centres will apply the following penalties for work submitted late:

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of five working days;
• where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/cqsd-old-site-documents/penaltiesforlatesubmission.pdf
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Assessment requirements for a pass:

50% in coursework

Reassessment arrangements:

Resubmission of coursework report

Additional Costs (specified where applicable):

Text books: ÌýLaudonÌýandÌýLaudon, Management Information Systems : Managing the Digital Firm v14-16 (1292296569 9781292296562). Cost – v14 available (online) in university library. Ìý Text books: Gordon, K. (2013) Principles of Data Management: Facilitating Information Sharing. 2nd Edition. (1780171846 9781780171845). Cost 27.99 for paperback - available (online) in university library Ìý

Optional Ìý Ìý Ìý Ìý Optional

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Last updated: 22 September 2022