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8/8/2019 CS5500 Session 01 AT2
1/24
CS5500 Data Management and
Business Intelligence
Session 1:
Module Overview . . .
Data, Information and Knowledge in Business
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Who am I?
Dr Allan Tucker, Brunel University:
Research Lecturer
Research Interests:
Data Mining
Machine Learning
Artificial Intelligence
Bayesian Networks
Time Series
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Session Learning Outcomes
The learning outcomes for this session are
that you:
Know the module learning outcomes, structure
and forms of assessment
Recognise the value, role and conceptual
difficulties associated with data, information and
knowledge in business environments
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Part 1
Module Overview . . .
A Reminder to Read the Study Guide!
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Module Aim
The aim of the module is to:
Develop knowledge and skills to support the
development of business intelligence solutions in
modern organisational environments
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Module Learning Outcomes
The learning outcomes for CS5500 are:
1.Describe and discuss the key concepts of data
management and business intelligence their value and
implications for information systems development anduse.
2.Apply the appropriate practical skills/abilities required
to implement business intelligence solutions
3.Reflect critically on the theory and appropriate use ofdata management and business intelligence in
organisational environments.
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Module Structure
The structure of the module is thus:
Session Lecturer Workshop
1 Data, Information and Knowledge Dr. Allan Tucker SAP BW Orientation
2 Data Warehousing (I) Relational Design Dr. Allan Tucker Reporting and QueryDefinition
3 Data Warehousing (II) Data Integration Dr. Allan Tucker Exception Reporting
4 Data Warehousing (III) Architectures Dr. Allan Tucker Creating SAP BW
InfoObjects
5 Data Warehousing (IV) Information Modelling Dr. Allan Tucker Creating SAP BW
InfoCubes
6 Datamining (I) The Concepts Dr. Allan Tucker Master Data Staging
7 Datamining (II) Advanced Analysis Dr. Allan Tucker Loading Transaction Data
8 Break out / Datamining (III) and Business
Intelligence
Dr Allan Tucker
Prof. Xiaohui Liu
Visualising and Analysing
Data (I)
9 Business Intelligence: Strategy and Practice Guest Visualising and Analysing
Data (II)
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Assessment
CS5500 is assessed wholly by coursework:
Coursework details Structured essay (1500 words) addresses Learning Outcomes 1
and 3 Technical appendix containing outputs of SAP BW workshops + 500-
1000 words of integrating text - addresses Learning Outcome 2
Brunel submission For both full and part-time students . . .
Submission 05/04/09 at 23.00 GMT via u-Link
NITH submission Full-time student submission 25/01/09 at 23.00 GMT
Part-time student submission 15/02/09 at 23.00 GMT
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Reading Material
The reading for the module is:
Core Virtual study pack (see Web base on u-Link)
Supplementary Connolly, T. and Begg, C. (2005), Database Systems: A Practical
Approach to Design, Implementation and Management, 4th Edn.,Addison Wesley, Essex.
Hand, Mannila, Smyth (2001), Principles of Data Mining, MIT Press
MacDonald, K., Wilmsmeier, A., Dixon, D. C. and Inmon, W. H.(2005), Mastering the SAP Business Information Warehouse:
Leveraging the Business Intelligence Capabilities of SAPNetWeaver, Wiley, New York.
Howson, C. (2008) Successful Business Intelligence: Secrets toMaking BI a Killer App, McGraw-Hill
Galit Shmueli, Nitin R. Patel, Peter C. Bruce (2007) Data Mining forBusiness Intelligence, Wiley.
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Brunel Contact Details
Contact details are:
Dr. Allan Tucker ([email protected])
Room SJ128h in St. Johns
Post questions to u-Link discussion board
Surgery hour 13.00 14.00 on a Wednesday
Meetings by appointment . . .
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Part 2
Data, Information and Knowledge in Business
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Hypercompetition in Business
Competitive advantage is difficult to sustain: Traditional business model
Legally restrain competition
Segment market to avoid head-to-head competition Build barriers to entry . . .
Many challenges now exist
Customer taste changes
Rapid technological change
Globalisation of markets Global alliances in many industries
Advantage is thus continually created, eroded,destroyed and recreated
Slide 12CS5550 Session 01
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Some Theories on Response
Management/IS theories emerging as a
response to rapidly changing environments:
Enterprise agility
Sensing and responding
Dynamic capabilities
Ability to integrate, build and reconfigure internal
and external competencies
Absorptive capacity
Organisational routines and processes by which
firms deal with knowledge
CS5550 Session 01 Slide 13
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Sensing and Responding
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Responding Intelligently
Some definitions of intelligence:
The ability to acquire and apply knowledge and
skills (OED)
The ability to learn, understand and make
judgments orhave opinions that are based on
reason (Cambridge)
The ability to apply knowledge to manipulate
one's environment (Merriam-Webster)
CS5550 Session 01 Slide 15
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The Data Explosion
If you feel like you are drowning in
information, its because you are.
Advance of IT and the Internet
Massive increase in ability to:
Record: Electronic records and forms
Store: Data Warehouses (more of this later) Analyse: Data Mining and Visualisation (more later)
Risk of Information Overload
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Problems with Core Concepts
A note of warning: Typical hierarchical view
Data as the raw material
Information as structured data Knowledge as personalised information
Inverse view
Knowledge must exist before information can beformulated and before data can be used to forminformation
Potential implications
Knowledge does not exist outside of an agent
Shaped by needs and initial stock
CS5550 Session 01 Slide 17
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Toward the Utopian Organisation
The emerging response to hypercompetitionequates to business intelligence:
Corporate performance management
Measure, decide and react . . . (backward BI)
Proact to adapt strategy, goals and process . . . (forward BI)
Flexible technology infrastructure and architecture
Processes not application specific
Service-orientation
Managing time-to-action
Data latency, analysis latency and decision latency
Business Intelligence = Data Integration + Data Mining &OLAP
Slide 18CS5550 Session 01
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An example
A primer for thought on business
intelligence:
Fighting crime with zeros and ones . . .(http://www-03.ibm.com/innovation/us/adv/special/overview/nypd/ high_wmv.html)
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Components of BI Architecture
Slide 20CS5550 Session 01
Some Jargon: Source Systems (Enterprise Resource Planning systems)
Extract Transform Load Data Warehouses & Data Marts
Querying and Reporting
On Line Analytic Processing
Data Mining
Dashboards
See Glossary in Study Guide!
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SAP BWWarehousing Solution
CS5550 Session 01 Slide 21
Source: SAP AG
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Session Summary
This session has examined the:
Module learning outcomes, structure and forms of
assessment
Value, role and conceptual difficulties associatedwith data, information and knowledge in business
environments
Understanding of business intelligence
CS5550 Session 01 Slide 22
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Key Reading
Key reading:
Study pack to support concepts discussed (e.g.,):
Anderson (1999)
Overby et al. (2006)
Tuomi (1999)
Zahra and George (2002)
Next Session : Relational Models
Chapters 3, 4 and 5 in Connolly and Begg (2005).
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Workshops
Thursdays: 11am - 1pm
Fridays: 2pm - 4pm
Allocations of Students to workshop sessions on U-Link
Students work in pairs though both are given accounts
Workshop 1: SAP BW Orientation (BSI need not attend)
From Workshop 2 it will be necessary to document yourwork see Assessment on U-Link