| This paper introduces the definition, character, history & developmental direction of the Data Warehouse and the essential technology of developing the Data Warehouse such as: granularity, decollation of data, the developing method & data model of the Data Warehouse, management of the metadata, data integrating, online analytical processing & data mining, data increment addition, etc. It also introduces how to complete 5 research assignments with those technologies in detail:(1) Build the Visual Modeling Tool of Data Warehouse; with the Modeling Tool, we bring forward the multi-fact table structure as the data model of the Soy Planting Data Warehouse;(2) With the database technologies such as ADO,SQL-DMO etc, we build the ETL Tool and with it achieve extraction, transformation & load of a great deal of data about soy planting which stored and organized by different styles, build the Soy Planting Data Warehouse;(3) We also complete querying data, making graph, calculating statistics, polynomial regression and so on;(4) Complete data increment addition and inputting data manually;(5) Accomplish enterprise-level management of the metadata.This system was designed into three-tier architecture. It can integrate many kinds of data-source (relational or not), such as Microsoft Access, Excel, etc. It also can integrate the data which stored in local computer or terminals. It has a very kind interface, completing building new Data Warehouse and data increment addition with guide process. The software has a strong capability of handling errors. Having a good capability of extension, it can be used in building the Soy Planting Data Warehouse which adopt Snowflake model or star model as its data model. Also having a good capability of extension, it can be used in building the Planting Data Warehouse of other plant such as wheat, rice etc. |
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