Data management approach instead of traditional file processing. Traditional method leading to 4 main problems, there are data redundancy, lack of integration, data dependence and lack of standardization.
Evolution of Data management technology (DBMS) technology
In the 1960s, network and hierarchical systems such as CODASYL and IMSTM were the state-of-the -art technology for automated banking, accounting, and order processing systems. Their basic architecture mixed the physical manipulation of data with its logical manipulation
A revolutionary paper by Codd in 1970. Codd's relational model introduced the notion of data independence, which separated the physical representation of data from the logical representation presented to applications. Data could be moved from one part of the disk to another or stored in a different format without causing applications to be rewritten. Application developers were freed from the tedious physical details of data manipulation, and could focus instead on the logical manipulation of data in the context of their specific application.
The foundation of the DBMS platform is a state-of-the art database architecture that seamlessly provides both relational and native XML as first class data models. That database technology provides the strongest foundation for an information integration platform for three significant reasons
First, DBMSs have proven to be hugely successful in managing the information.DBMSs deal quite naturally with the storage, retrieval, transformation, scalability, reliability, and availability challenges associated with robust data management.
Secondly, the database industry has shown that it can adapt quickly to accommodate the diversity of data and access patterns introduced by e-business applications over the past 6 years.
Thirdly, a platform that exploits and enhances the DBMS architecture at all levels is in the best position to provide robust end-to-end information integration.
In the 1970s, the data-processing department was not able to handle huge backlogs of requests for data analysis. Applications data was hidden behind mainframe files and databases, and it was periodically recorded in tapes for specific information manipulation.
Since the 1990s, data warehousing has become the most feasible solution to optimize and manipulate data (DBMS) . The current practice is to gather the data that is needed in an optimized database, regardless of the number of different applications and different platforms that are used to generate the source data.
Links:
techiezone.in/random/what-is-a-data-warehouse
www.dkms.com/papers/archev.pdf
http://www.ibm.com/developerworks/data/library/techarticle/0206roth/0206roth.html#evolution
http://www.information-management.com/news/946-1.html
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