Data Access within the Warehouse
The Ins & Outs (and everything in
between) of Data Warehousing
Jeff Byard
Donovan Schneider
Red Brick Systems, Inc.
https://www.wendangku.net/doc/e62500572.html,
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Ins and Outs of Data Warehousing
Goals
aHighlight differences with OLTP
aSummarize major aspects of data warehousing
aIdentify research opportunities
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Ins and Outs of Data Warehousing
Terminology
aOLTP (On-Line Transaction Processing)
aDSS (Decision Support System)
aDW (Data Warehouse)
aOLAP (On-Line Analytical Processing)
>ROLAP (Relational OLAP)
>MOLAP (Multi-dimensional OLAP)
>MDDB (Multi-dimensional Database)
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Ins and Outs of Data Warehousing
Topics of Discussion
aDifferences with OLTP
aWarehouse Architectures and Applications
aSchema Design
aPopulating the Warehouse
aData Storage within the Warehouse
aData Access within the Warehouse
aClient Analysis
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Ins and Outs of Data Warehousing
Optimized Data Warehouse RDBMS
Trend: Network Realities
aProliferation of data warehouse applications is
cost effective
aOrganization units require different levels of
analysis and information granularity
>different data
>different subsets
>different summarization levels
>different time periods
aInformation-based business partnerships
require shared data
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Ins and Outs of Data Warehousing
Data Warehousing is Critical to Business Success
Consumer Packaged Goods
Retail
Telecommunications
Healthcare Transportation/Distribution
Financial Services Data Service Providers promotion analysis category management call/rate usage analysis claims analysis
logistics management consumer credit analysis value-added data analysis
Many Industries Many Applications
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Ins and Outs of Data Warehousing
Trend: Smart Applications
aClosed-loop feedback applications
>inventory automation —> smart inventory stocking
>purchase order —> supplier analysis
aMass data analysis capability enables new
applications
aClose-coupled OLTP and data warehouse
create potential for new levels of automated
management decision process
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Ins and Outs of Data Warehousing
Typical Dimensions
l Time periods
l Geographic region (markets, cities)
l Products
(UPC, part numbers)
l Promotions (Discounts)
l Customers (Account number)
l Sales rep, buyer l Frequent flier, stayer
l Service level, procedure, operation
l Room type, service, classification, seat
l Drug, medicine
l Vendors, distributor, warehouse
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Ins and Outs of Data Warehousing