Data Warehouse, DSS, and BI Frameworks: Key Concepts

Data Warehouse Development Approaches

Kimball ApproachInmon Approach
EffortData Mart Approach

EDW Approach

ScopeOne Subject AreaSeveral Subject Areas
Development TimeMonthsYears
SourcesOnly Some Operational and External SystemsMany Operational and External Systems
Data TransformationsLow to MediumHigh
Update FrequencyHourly, Daily, WeeklyWeekly, Monthly
Development Cost$10,000 to $100,000+$1,000,000+
Development DifficultyLow to MediumHigh
Data Prerequisite for SharingCommon with Business AreaCommon 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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