MIS H2010 - Technology & Information Management 2

Module Details

Module Code: MIS H2010
Full Title: Technology & Information Management 2
Valid From:: Semester 1 - 2019/20 ( June 2019 )
Language of Instruction:English
Duration: 1 Semester
Credits:: 5
Module Owner:: Colin Cooney
Departments: Unknown
Module Description: An organization's data is recognised as the most vital asset of an enterprise. It is rightly said that companies who do not understand the importance of data management are less likely to survive in the modern economy. The ability to look at the volumes of data created by companies and to pull insight and analysis so that companies can make faster strategic decisions.
This module aims to enable students to understand the importance of data and knowledge management to the efficiency and productivity of an organisation and it how critical it is that organizations manage their data, information and knowledge effectively. The module also examines the impact of the Internet, mobile technologies and other innovative technologies as global strategic business tools.
 
Module Learning Outcome
On successful completion of this module the learner will be able to:
# Module Learning Outcome Description
MLO1 Demonstrate an understanding of how to collect, integrate and analyse business data and employ business intelligence tools to support evidenced-based decisions to drive business change and improve business processes.
MLO2 Appraise the managerial challenges faced by organisations wishing to commercially exploit database and knowledge management technologies.
MLO3 Critically evaluate the contribution Business Intelligence and Decision Support Systems make to management decision making.
MLO4 Assess the potential impact of the Internet and mobile technologies as global strategic business tools and evaluate the growing range of business models for e-business.
MLO5 Differentiate between a number of alternative systems acquisition methodologies.
MLO6 Design and develop a small relational database.
Pre-requisite learning
Module Recommendations
This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named DkIT module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
No recommendations listed
 
Module Indicative Content
Data Analytics Lifecycle
Key roles in the data analytics process, discovery (resources, stakeholders, developing hypotheses, potential data sources), data preparation (analytics sandbox, data inventories, data conditioning, “dirty” data), model planning, selection & building, visualisation & communication, operationalising & monitoring results.
Managing Data Resources
Data structures, data modelling, DBMS facilities, data warehousing, data marts & data Mining & OLAP, database development.
Managing Knowledge
Dimensions of knowledge, knowledge management value chain, types of knowledge management systems, collaboration & social tools and learning management systems, intelligent techniques, machine learning, deep learning, artificial intelligence.
Business Intelligence & Enhancing Decision Making
Managerial decision making, decision support technologies, expert systems, business intelligence applications, Decisions types & process, supporting the management activities & decision making, business intelligence & business analytics, groups descision support systems, geographic information systems.
The Internet & e-Business
e-Commerce & e-Business, viable Business Models, e-Business strategies, Web 2.0 & 3.0 tools, m-Commerce, supporting technologies, payment systems, revenue models, digital strategy, search engine marketing, social media.
Information Systems Acquisition & Development
Planning & justifying information systems, systems development life cycle and alternative methodologies, agile development, vendor and software selection, total cost of ownership.
Innovative Technologies
Emerging digital, intelligent and mesh technologies such as FinTech, distributed ledger technology (blockchain), augmented & virtual reality, digital twin, quantum computing, empowered edge, etc.
Module Assessment
Assessment Breakdown%
Course Work30.00%
Final Examination70.00%
Module Special Regulation
 

Assessments

Full-time

Course Work
Assessment Type Continuous Assessment % of Total Mark 30
Marks Out Of 0 Pass Mark 0
Timing S1 Week 11 Learning Outcome 6
Duration in minutes 0
Assessment Description
This individual continuous assessment will normally consist of the design and development of an appropriate small relational database to meet a set of specified information requirements.
No Project
No Practical
Final Examination
Assessment Type Formal Exam % of Total Mark 70
Marks Out Of 0 Pass Mark 0
Timing End-of-Semester Learning Outcome 1,2,3,4,5
Duration in minutes 0
Assessment Description
End-of-Semester Final Examination
Reassessment Requirement
A repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.

DKIT reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full-time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Facilitated learning using a variety of interactive pedagogical techniques. Every Week 2.00 2
Practical Contact Practical laboratory based classes. Every Week 1.00 1
Directed Reading Non Contact Prescribed readings as directed to supplement lecture material. Every Week 3.00 3
Independent Study Non Contact Wider reading and reflection on the subject area using a variety of methods. Particular focus will be placed on application of learning. Every Week 3.00 3
Total Weekly Learner Workload 9.00
Total Weekly Contact Hours 3.00
Workload: Part-time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Facilitated learning using a variety of interactive pedagogical techniques. Every Week 1.00 1
Practical Contact Practical laboratory based classes. Every Week 1.00 1
Directed Reading Non Contact Prescribed readings as directed to supplement lecture material. Every Week 4.00 4
Independent Study Non Contact Wider reading and reflection on the subject area using a variety of methods. Particular focus will be placed on application of learning. Every Week 3.00 3
Total Weekly Learner Workload 9.00
Total Weekly Contact Hours 2.00
 
Module Resources
Recommended Book Resources
  • Laudon K. & J. Laudon. (2019), Management Information Systems: Managing the Digital Firm, 16th. Pearson Education, [ISBN: 0135191793].
Supplementary Book Resources
  • O'Brien J. & G. Marakas. (2017), Management Information Systems, 10th. McGraw-Hill Higher Education, [ISBN: 125902671X].
  • Turban E. & D. King. (2015), Information Technology for Management: Digital Strategies for Insight, Action, and Sustainable Performance, 7th. Pearson Education, [ISBN: 1118897781].
This module does not have any article/paper resources
Other Resources