Data Warehouse, DSS, and BI Frameworks: Key Concepts
Data Warehouse Development Approaches
Kimball Approach | Inmon Approach | |
---|---|---|
Effort | Data Mart Approach | EDW Approach |
Scope | One Subject Area | Several Subject Areas |
Development Time | Months | Years |
Sources | Only Some Operational and External Systems | Many Operational and External Systems |
Data Transformations | Low to Medium | High |
Update Frequency | Hourly, Daily, Weekly | Weekly, Monthly |
Development Cost | $10,000 to $100,000+ | $1,000,000+ |
Development Difficulty | Low to Medium | High |
Data Prerequisite for Sharing | Common with Business Area | Common Across Enterprise |
Main Components of a Decision Support System
Other Computer-Based Systems <–> Internet, Intranets, Extranets
|
Data Management <–> Model Management <–> External Models
Knowledge-Based Subsystems
User Interface
Organizational Manager (User)
Knowledge-Based Management Subsystem:
Advanced DSS are equipped with a component called a
knowledge-based management subsystem that can supply
the required expertise for solving some aspects of the
problem and provide knowledge that can enhance
the operation of other DSS components.
Sensitivity Analysis, What-If Analysis, and Goal Seeking
Sensitivity Analysis:
A study of the effect of a change in one or more input variables on a proposed solution.
What-If Analysis:
A process that involves asking a computer what the effect of changing some of the input data or parameters would be.
Goal Seeking:
Asking a computer what values certain variables must have in order to attain desired goals.
Multiple Goals:
Refers to a decision situation in which alternatives are evaluated with several, sometimes conflicting, goals.
Key Issues About Data Management in Decision Support Systems
Data quality, data integration, scalability, and data security.
Factors Affecting Architecture Selection
Technical issues, social/political factors, constraints on resources,
nature of end-user tasks and upper management’s information needs
4 phases of decision-making process
intelligence phase:
the initial phase of problem definition in decision making
design phase:
involves finding possible alternatives in decision making
and assesing their contribution
choice phase:
alternatives is selected
implementation phase:
involving actually putting a recommenede soulution to work
components of business intelligence framework
data loading fields of business anaytics
| riporting anaysis
data sources data warehouse – decision support – results
| data mining |
visualisation visualisation
–data warehouse: originally, included historical data that were organized and summarize, so end users could easily view or manipulate data and information. today some data warehouse include current data as well. so they can provide real time decision support
–business analytics: reporting and queries/ advance analytics/ data, taxt and web mining and other sophisticate mathematial and statistical tools
–business perdormance management: an advance performance measurement and analysis approach that embraces planning and strategy
compare data warehouse architecutres
centralized integrared data withdirect access:
prons: business enterprise view, design consistency and data quality, data reusability
cons: requires corporate leadership and vision
dependent data marts:
prons: allows easier customization of user interfaces and reports
cons: business enterprice view challenging, redundant data costs, high DBA and operational costs, data latency
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