Summary
This chapter described in detail the usage of a Conditional Split data transformation.
You should use this generic task wherever you want to branch out based on
some business logic. This logic can be something that is a part of the data itself,
or some external conditions. Although the split data was channeled to three
Recordset Destinations, one may very well use other types of destinations as well.
In further chapters, we will see how the variable used in the Recordset Destination
transformation can be used (at present it is showing the number of rows that are
held therein).
Using an Aggregate Data
Transformation
This chapter shows you how to create a package that can aggregate data for a given
group of items in a Data Flow using the Aggregate Data Flow Transformation.
You will also learn how to use the Percentage Sampling Data Flow Component.
The data will be extracted from SQL Server 2005 and loaded to an in-memory
Recordset Destination.
Structured Query Language's SELECT query is perhaps one of the most important
statements that helps in identifying a single piece of information from a large
database. In developing enterprise reports, there are often times you need to know
consolidated specific pieces of information. For example, as a hiring manager you
may be interested in knowing the average and minimum salaries you have to pay
in a given geographical region for hiring. SQL provides the aggregate functions to
address those kinds of questions to the database by working on multiple records of
data.
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