In this post we will discuss about how to
check data errors using mappings and how to handle these errors.In Datawarehouse Mapping we come across
different kinds of errors.It depends on us that what kind of errors we want to capture
and should we reload or correct these errors and also how to store them.
Data must be checked before loading to
target table. One method is to use database Constraints or to use mappings to
capture errors.
Using Mapping
approach we can identify the data content errors and give the
appropriate descriptions and then re route these errors to error table. Error
table makes the analysis of captured errors easier and also improves the performance.
This can be effective for errors like null fields, incorrect data types or date conversions.
Once we have captured the error, the next
step is to separate these errors from the pipeline. We can do this using a
Router Transformation which will
route the error into a separate Error table (ERR_TBL).This Error table
will hold the information about the error like,
- The Mapping name from which the error came.
- The ROW ID of the record
- Descritption about the error
"We can make this approach in the form of a Mapplet and use it repeatedly in several
mappings and hence reduce the complexity and make the error detection easier"
Once we capture the data, the Business Team needs to decide whether we need
to correct the data and reload it or not. Using the Mapping approach we can
capture all the data errors and constraint errors and the business users can analyze
the errors more effectively.
Please share your valuable comments......
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