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IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 Data-Driven Business Intelligence Systems: Part II Week 6 Dr. Jocelyn San Pedro School of Information.

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Presentation on theme: "IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 Data-Driven Business Intelligence Systems: Part II Week 6 Dr. Jocelyn San Pedro School of Information."— Presentation transcript:

1 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 Data-Driven Business Intelligence Systems: Part II Week 6 Dr. Jocelyn San Pedro School of Information Management & Systems Monash University

2 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 2 Lecture Outline  On-Line Analytical Processing (OLAP)  Executive Information Systems (EIS)  EIS Development Framework

3 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 3 Learning Objectives At the end of this lecture, the students will  Have understanding of On-Line Analytical Processing (OLAP) and Executive Information Systems  Have understanding of executive information needs  Have knowledge of EIS development

4 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 4 On-Line Analytical Processing (OLAP)

5 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 5 On-Line Analytical Processing  Term coined by Codd to highlight differences between transactional processing and analytical processing  Transactional processing of operational data not suitable for answering managerial questions  Provides conceptual and intuitive model  Provides data retrieval at the “speed of thought”  FASMI Test by Pendse (2003)  12 Rules by Codd, Codd & Salley (1993)  OLAP Council

6 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 6 On-Line Analytical Processing CharacteristicsOLAPOLTP OperationAnalyseUpdate Screen formatUser-definedUnchanging Data transactionConsiderableLittle Level of detailAggregateDetail TimeHistorical, current, projected Current OrientationAttributesRecords

7 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 7 On-Line Analytical Processing FASMI Test by Pendse (2003)  Fast  Analysis  Shared  Multidimensional  Information http://www.olapreprt.com/fasmi.htm

8 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 8 On-Line Analytical Processing 12 OLAP Rules by Codd, Codd & Salley (1993) Multidimensional viewDynamic sparse matrix handling Transparent to the userMulti-user support AccessibleCross-dimensional operations Consistent reportingIntuitive data manipulation Client/server architectureFlexible reporting Generic dimensionalityUnlimited dimensions, aggregation

9 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 9 On-Line Analytical Processing Storage paradigms to support OLAP  Desktop OLAP (DOLAP) – desktop files  Relational OLAP (OLAP) – relational database servers  Multidimensional OLAP (MOLAP) – multidimensional database servers

10 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 10 On-Line Analytical Processing

11 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 11 On-Line Analytical Processing Gray and Watson (1998)

12 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 12 On-Line Analytical Processing Representative OLAP / Multidimensional Analysis Packages  BrioQuery (Brio Technology Inc.)  Business Objects (Business Objects Inc.)  Decision Web (Comshare Inc.)  DataFountain (Dimensional Insight Inc.)  DSS Web (MicroStrategy Inc.)  Focus Fusion (Information Builders Inc.)  InfoBeacon Web (Platinum Technology Inc.)  Oracle xpress Server (Oracle Corporation)  Pilot Internet Publisher (Pilot Software Inc.)  Cognos Reportnet (Cognos)

13 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 13 On-Line Analytical Processing Cognos ReportNet

14 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 14 Hypherion’s Business Performance Management

15 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 15 Executive Information Systems (EIS)

16 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 16 Executive Information Systems  Intended to provide current and appropriate information to support executive decision making  Emphasis is on graphical displays, easy-to-use interface  Designed to provide reports or briefing books to top-level executive  Strong reporting and drill-down capabilities

17 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 17 Executive Information Systems  Shared decision support systems  Can only support ‘recurring’ information requirements  Very high profile  Relatively expensive

18 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 18 Executive Information Systems  Tailored to individual executive users  Designed to be easy to operate & require little or no training  Focussed on supporting upper-level management decisions  Can present info in graphical, tabular & text  Provides access to info from broad range of internal & external sources  Provides tools to elicit, extract, filter, & track critical information  Provides a wide range of reports including status reporting, exception reporting, trend analysis, drill down investigation, & ad hoc queries

19 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 19 Executive Information Systems What an EIS is NOT  It is not a substitute for other computer-based systems. The EIS actually feeds off these systems.  It does not turn the executive suite into a haven for computer “techies”.  It should be viewed by senior management as a trusted assistant who can be called on when and where necessary.

20 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 20 Executive Information Systems Why Are Top Executives So Different?  They are enterprise-oriented in thinking  The possess the broadest span of control  They are responsible for establishing policy  They represent the organization to the external environment  Their actions have considerable financial and human consequences

21 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 21 Executive Information Systems Why Are Top Executives So Different?  They are enterprise-oriented in thinking  The possess the broadest span of control  They are responsible for establishing policy  They represent the organization to the external environment  Their actions have considerable financial and human consequences

22 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 22 Executive Information Systems Executive Information Needs  Disturbance management may require around-the-clock attention.  Entrepreneurial activities require the executive to predict changes in the environment.  Resource allocation tasks require the manager to choose when and where the limited resources are deployed.  Negotiation requires up-to-the-minute info to help build consensus.

23 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 23 Executive Information Systems Frequency of Executive Activities

24 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 24 Executive Information Systems Methods for Determining Information Needs Rockart identified five basic methods for determining information needs:  By-Product Method  Null Method  Key Indicator Method  Total Study Method  Critical Success Factors Method

25 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 25 Executive Information Systems Critical success factors  Concentrate on the most important information requirements  Common technique  Critical success factors (CSF’s) are the few key areas where things must go right in order to achieve objectives and goals  Critical failure factors (CFF’s) are the factors whose existence or lack of existence can contribute to failure

26 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 26 Executive Information Systems Key Performance Indicators  How do you know how well you are doing against your CSFs? KPI’s  A KPI is a measurement that tells us how we are performing in regard to a particular CSF.  A single CSF may have multiple KPI’s  An EIS is a useful tool for assessing KPIs, and therefore for understanding CSFs.  By concentrating on these critical factors, we have a starting point for systems analysis – we know that CSFs and their KPIs are going to be mandatory information requirements.  Provides structure for requirements elicitation interviews.

27 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 27 Executive Information Systems General CSF interview approach  Explanation of CSF interview objectives  Interviewee is asked to:  Describe organisational mission and role  Discuss goals  CSF’s are developed  CSF’s priorities are determined  Measures are developed (KPI’s)

28 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 28 Executive Information Systems CSFs & KPI’s in an EIS

29 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 29 External Data Data Cubes The EIS Executive Workstation The Data Warehouse OLAP From Here To Here Executive Information Systems Report Templates Relationship of OLAP to EIS Architecture

30 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 30 Executive Information Systems

31 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 31 Executive Information Systems

32 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 32 EIS Development Framework

33 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 33 An EIS Development Framework Watson, et al suggest a framework with three components: 1.Structural perspective: focus is on people and data as they relate to the EIS. 2.Development process: the dynamics and interactions are identified. 3.User-system dialog: contains an action language for processing the commands.

34 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 34 An EIS Development Framework Some EIS Limitations and Pitfalls to Avoid  Cost: a 1991 survey showed an average development cost of $365,000 with annual operating costs of $200,000.  Technological limitations: the EIS needs to be seamlessly integrated into the company’s current IT architecture, so it is a formidable challenge to the designer.  Organizational limitations: the organizational structure might not be right.

35 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 35 An EIS Development Framework Organizational Limitations  Agendas and time biases: the EIS represents only part of executive’s total agenda, and it may become easy to be overly reliant on it.  Managerial synchronization: heavy reliance on the timely, ad-hoc, EIS reports may disrupt stable, well- established reporting cycles.  Destabilization: fast EIS response may cause the executive to react too swiftly, leading to less stability in the organization.

36 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 36 An EIS Development Framework Failure is not an Acceptable Alternative Some factors that contribute to EIS failure:  Lack of management support  Political problems  Developer failures  Technology failures  Costs  Time

37 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 37 An EIS Development Framework The Future of Executive Decision Making and the EIS Several conditions will merge to transform the technology. Some are easy to predict, some not. Two that we can foresee are:  Increased comfort with computing technology in the executive suite will make innovations more readily accepted.  Broadening of executive responsibilities will broaden the demand for information.

38 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 38 An EIS Development Framework The EIS of Tomorrow  The intelligent EIS: advances in AI technology will be deployed in the EIS  The multimedia EIS: multimedia databases will allow future integration of text, voice and image  The informed EIS: future EISs will make wider use of data external to the company  The connected EIS: high-bandwidth communication allows greater interconnectivity

39 IMS3001 – BUSINESS INTELLIGENCE SYSTEMS – SEM 1, 2004 39 References  Codd, E.F., Codd, S.B., & Salley, C.T. (1993). Providing OLAP (On-line Analytical Processing) to User-Analysts: An IT Mandate. E. F. Codd & Associates at.  Gray P. and Watson, H. (1998) Decision Support in the Data Warehouse, Prentice Hall.  Marakas, G.M. (2002). Decision support systems in the 21st Century. 2nd Ed, Prentice Hall  Pendse, N. (2003) What is OLAP? The OLAP Report, http://www.olapreprt.com/fasmi.htm http://www.olapreprt.com/fasmi.htm  Vitt, E., Luckevich, M. and Misner, S. (2002) Business Intelligence, Microsoft Corporation.


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