A major portion of
applications outgrow their data structure. The data structure whether
it is file based or table based may have become antiquated. The new
operating system upgrade may no longer support the old environment.
The company has changed database vendors and has mandated all
applications be switched to the new platform.
These are but a few of the reasons for needing to convert data. The
process involves reading data from the old files.and writing the data
out to the new data base/data structure. Business Application Developers can write routines to read database schemas in one format and create
new schemas in another. Routines can also be written to read the data
from the old data source and write to the converted files.
Another application of data conversion is database synchronization. This used where two or more databases need to share some data. One of the databases is recognized as the master of certain data and the other the recipient. By writing some synchronization software, the database data can be kept current between the two databases on an ongoing basis using regularly scheduled synchronization jobs.
The key to any synchronization effort is mapping the data between the two databases. The mapping should be kept flexible enough so that it may be easily modified when an altered or additional mapping is desired. I prefer a table driven approach here as oppossed to the quick and dirty hard coding. The hard coding is is faster to write, but is inflexible and difficult to maintain
