Information Technology Reference
In-Depth Information
Chapter 4
Data Conversion
The objective of data conversion is to convert between database systems without
any loss of information. The data conversion process must transform the data from
one data structure to another whilst preserving its semantics. Data conversion uses
the data structure of the schema that results from schema translation.
As the relational model, object-oriented, and XML models become more popular,
there is a need to convert production nonrelational databases to relational databases,
and from relational databases to object-oriented databases and XML databases, i.e.,
XML documents stored in a native XML database or XML enabled database, to im-
prove productivity and flexibility. The changeover includes schema translation, data
conversion, and program translation. The schema translation consists of static data
structure transformation from nonrelational to relational schema or from relational
database schema to an object-oriented or an XML schema. This chapter describes a
data conversion methodology to unload production nonrelational or a relational da-
tabase to sequential files, and then upload them into a relational, object-oriented, or
XML database. There are basically four techniques in data conversion: customized
program, interpretive transformer, translator generator, and logical level translation.
These are described in the following sections.
4.1
Customized Program Approach
A common approach to data conversion is to develop customized programs to trans-
fer data from one environment to another (Fry et al. 1978 ). However, the custom-
ized program approach is very expensive because it requires a different program to
be written for each M source file and N target, which sums up as m ᅲ n programs
for all of them. Furthermore, these programs are used only once. As a result, totally
depending on customized program for data conversion is unmanageable, too costly,
and time consuming.
Search WWH ::




Custom Search