Oracle Data Warehouse Tuning for 10g

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Oracle Data Warehouse Tuning for 10g

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內容描述

Description:

“This book should satisfy those who want a different perspective than the
official Oracle documentation. It will cover all important aspects of a data
warehouse while giving the necessary examples to make the reading a lively
experience.”- Tim Donar, Author and Systems Architect for Enterprise
Data WarehousesTuning a data warehouse database focuses on large
transactions, mostly requiring what is known as throughput. Throughput is
the passing of large amounts of information through a server, network and
Internet environment, backwards and forwards, constantly! The ultimate
objective of a data warehouse is the production of meaningful and useful
reporting, from historical and archived data. The trick is to make the reports
print within an acceptable time frame.A data model contains tables and
relationships between tables. Tuning a data model involves Normalization and
Denormalization. Different approaches are required depending on the
application, such as OLTP or a Data Warehouse. Inappropriate database design
can make SQL code impossible to tune. Poor data modeling can have a most
profound effect on database performance since all SQL code is constructed from
the data model.
 
Table
of Contents:

Contents at a GlanceChapter 1. Introduction to Data
WarehousingChapter 2. Data Warehouse Data ModelingChapter 3. Making
Hardware and I/O Perform in a Data WarehouseChapter 4. Data Warehouse
Physical ArchitectureChapter 5. Effective Data Warehouse
IndexingChapter 6. Constraints and Integrity in Data WarehousesChapter

1. Using Partitioning and Tuning Parallel ProcessingChapter 8.
   Materialized Views and Query RewritesChapter 9. Oracle Dimension Objects
   Chapter 10. Data Loading: Extraction and TransportationChapter 11.
   Data Loading: Loading and TransformationChapter 12. SQL Aggregation Using
   GROUP BY Clause ExtensionsChapter 13. Analysis Reporting Using Special SQL
   FunctionsChapter 14. SQL and the MODEL ClauseChapter 15. OLAP (Online
   Analytical Processing) and Mining the Redo Logs with Data
   MinerAppendices