DATA MANAGEMENT AND BUSINESS INTELLIGENCE. Module Code 5CC519 Pre-requisite: None

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1 Module Title DATA MANAGEMENT AND BUSINESS INTELLIGENCE Date of Approval June 2012 Module Code 5CC519 Pre-requisite: None Module Level 5 Credit value 20 Total Number 200 of Learning Hours Key Words Module Delivery Mode Databases, Information Technology, data-mining, business intelligence, prototyping Blended / Face to face Module Description The acquisition, validation, organisation, management, analysis, presentation and interpretation of data is the primary purpose of information systems in organisations. Underlying much of the success of information systems has been the development of the databases upon which modern information systems are built. The information systems professional needs to understand how these data systems work, how their benefits can be optimised and how to analyse and evaluate the information in the systems in order for the users and managers of the organisation can obtain maximum value for their investments in Information systems. A key problem for data management is to reconcile the conflicting demands for real-time data capture for operation systems with the needs of the for management analysis in Business Intelligence, Management Information and Executive Information system, thus introducing the concepts of data-warehouses. This module will expose students to a wide range of database and data analysis topics which will be actively and practically explored by the students in order to prepare them for their future careers in large and small organisations. They will have opportunities to work with representative, real-world datasets to develop their understanding of the issues involved in managing and analysing the data and to explore the practical aspects of data mining and management data analysis and presentation using the SAS product set, including the Business Intelligence engine. Module Learning Outcomes On successful completion of the module, students will be able to: 1. Identify and critically evaluate the key requirements for effective data management, analysis and presentation to meet users needs

2 2. Develop a small management information reporting system that meets the users needs using a prototyping / Agile approach Module Content The module will consider topics such as:- The principles of data analysis and normalisation as the foundation of the store once and once only principle for data integrity The principles of data administration and security management The requirements for optimisation of data management for the conflicting needs of real-time and MIS / EIS and BI purposes The impact of User-centred analysis and participatory development on the development data structures and stores and systems that meet the needs of the organisation The role, application and benefits of prototyping in the rapid development of systems, using RAD and Agile approaches Techniques and practices for effective data analysis and presentation The impact of cloud computing and storage on the management of and access to organisational data. Together with a range of current, leading edge topics and technologies that affect data management and usage. Module Learning and Teaching Methods The module will be taught using a weekly 2 hour computer lab based workshop where the foundations of the topic will be presented and the students will research and develop the concepts using the learning by doing approach, followed by 2 hour small group tutorial in computer labs, where the students will undertake problem based activities, creating, managing, analysing, presenting and interpreting real-world datasets using the SAS product set. Regular formative feedback will be provided in both workshops and tutorials. Lab based Workshops Lab based Tutorials Guided Independent Study Total: 24 hours 24 hours 152 hours 200 hours Module Assessment Mode: Coursework 100% Scheduled learning and teaching activities: 24% Guided independent study: 76% Placement/study abroad: 0%

3 Course Work 100% The module will be assessed by a single portfolio consisting of an individual application project supported by a short, business report which academically justifies the design decisions that underpin the finished application system, which will be built in the SAS environment.

4 Reading lists Key Texts - none Essential texts Aanderud, T. and Hall, A. (2012) Building Business Intelligence Using SAS: Content Development Examples, SAS Institute, ISBN-13: Collier, K.W., (2011) Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing: Delivering the Promise of Business Intelligence, Addison Wesley, ISBN-13: Other recommended reading Blenkhorn, D.L. and Fleisher, C.S. (Eds), (2005) Competitive Intelligence and Global Business, Westport, Conn. : Praeger ; Oxford : Harcourt Education, ISBN-13: Fernandez, G. (2010) Statistical Data Mining Using SAS Applications, Boca Raton, CRC Press, ISBN-13: Han, J., Pei, J., Kamber, M. (2012) Data Mining: Concepts and Techniques, London : Morgan Kaufmann, ISBN-13: Howson, C., (2008), Successful Business Intelligence: Secrets to Making BI a Killer App, McGraw-Hill Osborne, ISBN-13: Ishikawa, A. and Nakagawa, J. (2012) Introduction to Knowledge Information Strategy, An: From Business Intelligence to Knowledge Sciences, World Scientific Publishing, ISBN-13: Laursen, G.H.N. and Thorlund, J. (2010) Business Analytics for Managers: Taking Business Intelligence Beyond Reporting, Winchester, John Wiley & Sons (*) ISBN-13: Raisinghani, M.S (Ed.), (2004 ) Business Intelligence In The Digital Economy: Opportunities, Limitations And Risks, Hershey, Pa. : Idea ; London : Eurospan, ISBN-13: Refaat, M. (2006) Data Preparation for Data Mining Using SAS, Morgan Kaufmann, ISBN-13: Sabherwal, R. and Becerra-Fernandez, I. (2010) Business Intelligence, Chichester, John Wiley and Sons, ISBN-13: Van der Lans, R. (2012) Data Virtualization for Business Intelligence Systems, Morgan Kaufmann, ISBN-13:

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