Two-Tier DW Architecture. Three-Tier DW Architecture.

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Presentation transcript:

Two-Tier DW Architecture

Three-Tier DW Architecture

DW Components Data migration tools –Tools that help extract, transform and load data into the data warehouse –Three main categories Data copying and replication Data transformation Data cleansing Metadata usage –Administrative and end-user

DW Components Warehouse data stores –Structures used to actually store the data –Typically relational DB (but not always) –Multi-dimensional DB becoming more popular Data retrieval, formatting and analysis –Query tools –Analysis tools –Data mining Management tools –Access control, performance monitoring, usage monitoring

Steps in Data Warehousing 1.Identify all the sources of data 2.Design the data warehouse 3.Extract/Transform/Load process 4.Decision making from DW

DW Design: Star Schema Lots of records, but each record is “thin” Fewer records, but each record is “fat” (lots of big columns) Want to be able to “see” each Sale by Product, Time, Store “Fact” “Dimensions”

E/T/L Process Extract –Data must be extracted from source systems Transform –Cleansing Identify and eliminate data inconsistencies Can be very complex, expensive, time consuming –Aggregation Load –Must be repeated periodically –How often? –Identifying changed data

DW Process Overview