With the intensification of market competition and the development of information society needs, it is increasingly important to extract (retrieve, query, etc.) information from large amounts of data to formulate market strategies. This demand not only requires online services, but also involves a large amount of data for decision-making, and traditional database systems can no longer meet this demand. This is specifically reflected in three aspects:
The amount of historical data is huge.
Auxiliary decision-making information involves data from many departments, and data from different systems is difficult to integrate.
Due to insufficient ability to access data, its performance in accessing large amounts of data is significantly degraded.
With the maturity of C/S technology and the development of parallel databases, the development trend of information processing technology is to extract data from a large number of
transactional databases, clean and convert them into new storage Format is to aggregate data
in a special format for decision-making goals. As this process develops and improves, this special data
storage that supports decision-making is called a data warehouse (Data Warehouse, DW).
W. H. Inmon's definition of data warehouse is that data warehouse is a subject-oriented, integrated, stable, and different time data collection that supports the management decision-making process.
Theme is the standard for data classification. Each theme corresponds to an objective analysis area, such as customers, stores, etc. It can integrate large amounts of data from multiple departments and different systems for
assisted decision-making. The data warehouse contains a large amount of historical data, and the data that enters the data warehouse after integration is rarely updated. The data time limit in the data warehouse is from 5 to 10 years, and is mainly used for time trend analysis. The data volume of the data warehouse is very large, generally about 10GB. It is 100 times the data volume of a general database
(100MB), and large data warehouses reach TB levels.
Data warehouse is mainly used in two aspects:
Use browsing analysis tools to find useful information in DW.
The data warehouse system supports the application on DW to form a decision support system (DSS).
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