22797 Business Intelligence 1: Advanced Analysis

UTS: Business: Accounting
Credit points: 6 cp

Subject level: Postgraduate

Result Type: Grade and marks

Handbook description

This subject introduces students to concepts and application in data warehousing, one of the key topics in modern business information management. In times in which the filtering, aggregation and analysis of external (e.g. WWW) and internal information have become a critical success factor in business, data warehouses and analytical applications (OLAP) are booming and have become frequently used tools of many accountants, sales analysts, etc. This subject guides students through the complete data warehouse planning and implementation process, and familiarised them with the specifics of multi-dimensional reporting. SAP solutions are used in order to practise the procedures in data warehouse design and in order to demonstrate the application of information generated in data warehouses for management accounting and decision making.

Subject objectives/outcomes

On successful completion of this subject students should be able to:

understand how data warehouse systems differ from operational information systems
analyse the requirements for such systems from a management accounting perspective
transform that requirements definition into a conceptual data model which can be used in discussion with contractors/developers
implement the data model in a widely used data warehouse product (SAPs Business Warehouse)
define cleansing algorithms to ensure data quality and to syntactically and semantically reconcile data from different operational information systems which act as sources
define and implement a management accounting reporting scheme in the warehouse.

Contribution to graduate profile

Data Warehouse systems are designed to serve the needs in reporting, statistical analysis, and simulation for managerial decision-making. They are not a simple copy of the operational data; they are specifically prepared to the needs of decision support in that they store aggregates and provide a rich toolset for combining and analysing aggregate facts from different sources and parts of the company.

Teaching and learning strategies

A variety of teaching and experimental learning methods and strategies are applied, including teamwork, discussions, and, above all, hands-on experience with an ERP-system (SAP solutions).

Students are required to use the SAP BI system outside normal class hours. They have to work on a collaborative case study project, in order to gain the ability to apply their knowledge in a problem-oriented environment and to increase their teamwork and communication-skills. Each team member also has to make a short oral presentation of his/her contribution to the project.

Content

Introduction to data warehousing
Requirements definition, conceptual data model
Implementation of the data model in a widely used data warehouse product (SAPs BI)
Logistic data model, Star Schema and variations
Data loading and supervising from 'operational information system'
Definition and implementation of a reporting scheme in the warehouse.

Assessment

Assessment item 1: Mid-term exam (Individual)

Objective(s):	1, 2
Weighting:	20%
Task:	Assesses objectives 1 and 2

Assessment item 2: Case study (Group)

Objective(s):	3, 5
Weighting:	30%
Task:	Assesses the application component of the subject, covering primarily objective 3,5

Assessment item 3: Final exam (Individual)

Objective(s):	1-5
Weighting:	50%
Task:	Assesses – at the individual level – both the conceptual and application component of the subject covering all objectives

Required text(s)

Ossimitz, M.L. (2009): Data Warehousing with SAP BI

UTSOnline http://online.uts.edu.au

SAP Online Help http://help.sap.com

Faculty of Business (current version), Guide to Writing Assignments, Faculty of Business, University of Technology, Sydney.

Indicative references

Anahory, S., Murray, D. (1997): Data warehousing in the real world: a practical guide for building decision support systems; Addison-Wesley, Reading, Massachusetts.

Brackett, M. H., (1996): The data warehouse challenge: taming data chaos, John Wiley & Son, Inc. Brisbane, N.Y.

Egger, et.al (2007): SAP Business Intelligence, Galilio Press, Bonn Germany.

Golfarelli, M., Maio, D., Rizzi, S. (1998): Conceptual Design of data warehouses from E/R Schemas; in: Proceeding of Hawaii International Conference On System Sciences, January 6-9, 1998, Kona, Hawaii, http://www-db.deis.unibo.it/~srizzi/PDF/hicss98.pdf (accessed 8/8/2007).

Grant, G. (2003): ERP & data warehousing in organisations: issues and challenges. Hershey, PA : IRM Press.

Dunn, C.LJ, Cherrington, Owen. Hollander A.S. (2005): Enterprise information systems : a pattern-based approach, 3rd edition/ New York : McGraw-Hill/Irwin,

Jarke, M., Lenzerini, M., Vassiliou,Y., Vassiliadis, P., (2003): Fundamentals of Data Warehouses, Springer, Berlin, New York, 2nd, rev. and extended ed..

Kimball, R. and Ross, M. (2002): The data warehouse toolkit: the complete guide to dimensional modeling; John Wiley & Sons, New York.

McDonald, K., Wilmsmeier, A., Dixon, D.C. and Inmon, W.H. (2006): Mastering the SAP business information warehouse : leveraging the business intelligence capabilities of SAP NetWeaver, 2nd ed. ,John Wiley & Sons, Indianapolis, IN

Raden, N.(1996): Star Schema 101; Archer Decision Sciences, Santa Barbara, http://members.aol.com/nraden/str101_e.htm

Turban, Efraim (et.al) (2007) Decision support and business intelligence systems, Imprint Upper Saddle River, N.J. Pearson Prentice Hall, 8th ed.

Taniar, David (editor).(2006) Research and trends in data mining technologies and applications / Imprint Hershey PA : Idea Group Pub..

Wieder, B. (2007): Financial Accounting and ERP – Integrated Event-Accounting with SAPTM ERP, Tekniks Publ., Sydney. (available at KopyStop-Bookshop)

Focusing on the relational database aspect:

Kroenke, D.M. (2005): Database Processing: Fundamentals — Design — Implementation; 10th ed., MacMillan, New York.

Atzeni, P., De Antonellis, V. (1993): Relational Database Theory, The Benjamin/Cummings Publishing Company, Inc., Reading, Massachusetts.

Internet resources

Data warehouse providers, e.g. SAP AG: www.sap.com

Oracle www.oracle.com/applications

SAS GmbH www.sas.com

Education and Research in Enterprise-Systems at UTS/Business: www.business.uts.edu.au/accounting/courses/sap/

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