Data Mapping
Data mapping identifies the process of moving data from a field in
an individual file to another field in a second file. An example of
data mapping includes moving the value from a ‘name’ field
in a customer data base to a ‘customer name’ field in a
sales database. Data mapping is used in data integration where multiple
systems, each with different but often related data are being tied
together. A classic example of data mapping involves moving data received
through EDI to an ERP system. In this example the data mapping is taking
translated EDI data and copying the individual elements in specific
fields in tables of the ERP system. Through this data mapping the EDI
data becomes (for example) a purchase order in the ERP system. Data
mapping has proven very useful in reducing costs associated with manual
data entry.
Ways of Using Data Mapping
There are a number of ways of using data mapping. At the most basic
level, data mapping can be performed through creating custom applications
that move data between systems. The problem with this form of data
mapping is that it creates a fixed link between systems. Because of
this link, any change to the source or target system would require
changes to the data mapping program. More modern data mapping techniques
involve the use of purpose specific applications that are designed
for data mapping. This type of application allows for the data mapping
to be performed graphically through a process of dragging a source
element and dropping it onto its target element in the secondary file.
This new form of data mapping has proven easier to perform and to maintain,
making data mapping a business that by some accounts is growing by
as much as 30% per year.
Data Mapping Techniques
Transformation logic is one of the earliest techniques used in data
mapping and involves creating applications that are responsible for
data mapping. A new technique known as data driven data mapping evaluates
the data values in two different data sources simultaneously. This
type of data mapping is popular because of its ability to identify
exceptions that could not generally be discovered through data mapping
performed using transformation logic.
Semantic data mapping is similar to the auto-connect features used
in graphical data mapping. Semantic data mapping
uses a metadata registry to inquire about different
data element synonyms. This form of data mapping will only find exact
matches between two columns of data.
The Value of Data Mapping
These two advantages of data mapping are critical in understanding
the rapid growth of the data mapping market. As companies have employed
data mapping and realized the savings from it, demand for data mapping
applications has grown greatly. Through data mapping, companies of
all sizes can recognize significant financial benefits.
Data Mapping Streamlined
Those that do data mapping usually have their
preferred way to go about it. Some people like one type of data
mapping better than others, and other professionals will tell you
that the method of data mapping that they choose truly depends on
the type of document and document language that they are dealing with. Having
experience in all data mapping varieties is a great asset as it will
allow the data mapping specialist to call on all of their data mapping
experience to make each data mapping experience as streamlined as
possible. |
