The row count is stored in a variable associated with this transformation.
Row Sampling
This is very similar to percentage sampling transformation. The difference is that
you can choose the size of the dataset and you will get a randomly selected subset
of data. When you need to randomly choose a few rows from a large group, this is
ideal. Just as in the case of percentage sampling, the seed for random selection can be
chosen, or you can use a machine generated seed.
SSIS Basics
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Script Component
If you need data flow programming using all the power of.NET, then this is the
transformation to use. You can add script support for data flow to work at run time
using the powerful programming constructs in Visual Basic, complied and executed
at run time.
Slowly Changing Dimension
This transformation is used with both OLTP and OLAP to attend to changes that
take place in dimension tables or look up tables. When an attribute of a row changes
in either of these, there are situations when you want to keep the old value as well
as the new value. This transformation has been designed to address several kinds of
business needs, also known as change types. Some of the change types are: Changing
Attributes Updates Output (basically an overwriting of an existing record); Historical
Attribute (creating a new records instead of updating the records); and Fixed
Attribute (Keeping the value unchanged).
Sort
When you need columns to be sorted either in ascending, or in descending order,
this transformation can be used.
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