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Topics include in this course are Data Warehousing Concepts, Design and Development, Extraction, Transformation and Loading, OLAP Technology, Data Mining Techniques: Classification, Clustering and Decision Tree, Advanced Topics. This lecture includes: OLAP, Types, Analysis, Service, Architecture, Decision, Support, Systems, Model, Compare, Contrast, Star, Schema
Typology: Slides
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**1. Analysis Service Architecture/Three โ tier Decision Support Systems
Approaches to OLAP servers
Multi โ dimensional data model
ROLAP, MOLAP, HOLAP
Which to choose: Compare and Contrast**
Information Sources Data Warehouse Server(Tier 1) OLAP Servers (Tier 2) Clients(Tier 3) Operational DBโs Semistructured Sources extracttransformloadrefreshetc. Data Marts Data Warehouse e.g., MOLAP e.g., ROLAP serve OLAP Query/Reporting Data Mining serve serve
Almost always a relational
Relational
extended relational
that maps operations on multidimensional data to standard relational operators
Multidimensional
special
purpose server that directly implements multidimensional data and operations
Query and reporting tools
Analysis tools - Data mining tools
analyzing the effectiveness of a marketing campaign bymeasuring sales growth over a certain period
analyzing the impact of a price increase on the productsales in different regions and product groups during thesame period of time
Cube
OLAP: Revision of Important Concepts