Look at database mapping in xml

[mike myers]

Data mapping is to some degree, a complex and rapidly expanding subject, particularly within large, data led businesses. In this article, I will make an effort to summarize, in simple terms, exactly what is data mapping, the most effective options for conducting data mapping along with a swift summary of the available approaches / tools, and at last I'm going to outline several trade best practices.

Therefore let’s commence with a basic meaning of data mapping. Whilst there isn't any established dictionary definition the below functions as a adequate starting place.

Data mapping can be explained as the process of producing data element mappings amongst two particular versions, normally a source data in addition to a destination data with the data mapping process creating a connection or map among data fields in both data models.

The data model itself could be either metadata or any atomic unit of data files which have a precise meaning. Concerning performing a data mapping, this can be done in a number of ways, determined by your level of know-how and what equipment you've got available.


Data Mapping Methods

There are a selection of methods to carry out data mapping, common methods consist of employing procedural code, xslt transforms or through mapping tools or software which will automatically and programmatically make and also run executable transformation programs. Lets cover each of these approaches in more details.

Manual data mapping is basically connecting or mapping fields in one set of data with a equivalent field in another data set by basically pulling a line from one field to another. This is usually completed in some kind of graphical mapping tool which will automatically create the results not to mention execute the data transformation

Data driving mapping entails implementing advanced heuristics in addition to statistics to simultaneously evaluate data values in 2 sources to automatically complex mappings between the two data sets. What's more, it's on the list of most recent techniques for data mapping and is particularly valued for facilitating more intricate mapping procedures involving data sets such as discovering advanced transformations or elements ie substrings, arithmetic, case statements, concatenations etc.

Semantic data mapping is a lot like the auto-connect attribute of data mappers due to the fact it should take advantage of semantics to connect and map two sets of data, but it really cannot make use of the metadata registry to seek out or match synonyms. It is able to primarily uncover exact matches between data columns rather than any transformation logic or execptions.

More on data mapping at http://www.liquid-technologies.com/DataMapper/data-mapping.aspx