Datasheet

Chapter 1: Welcome to SQL Server Integration Services
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Sources can also be hand coded using two methods. One method is to use the Script Component to create
a source stream using the existing .NET libraries. This method is more practical for single - use applications.
If you need to reuse a custom source, you can develop one by extending the SSIS object model.
Destinations
Inside the Data Flow, destinations consume the data after the data pipe leaves the last transformation
components. The flexible architecture can send the data to nearly any OLE DB – compliant, flat - file, or
ADO.NET Data Source. Like sources, destinations are also managed through the Connection Manager.
The following destinations are available to you in SSIS:
Data Mining Model Training: Trains an Analysis Services mining model by passing in data
from the Data Flow to the destination.
ADO.NET Destination: Exposes data to other external processes, such as Reporting Services or
your own .NET application. It also uses the ADO.NET DataReader interface similar to the ADO
.NET Source to consume the data.
Data Reader Destination: Allows the ADO.NET DataReader interface to consume data similar
to the ADO.NET Destination.
Dimension Processing: Loads and processes an Analysis Services dimension. It can perform a
full, update, or incremental refresh of the dimension.
Excel Destination: Outputs data from the Data Flow to an Excel spreadsheet.
Flat File Destination: Enables you to write data to a comma - delimited or fixed - width file.
OLE DB Destination: Outputs data to an OLE DB data connection like SQL Server, Oracle, or
Access.
Partition Processing: Enables you to perform incremental, full, or update processing of an
Analysis Services partition.
Raw File Destination: Outputs data in a binary format that can be used later as a Raw File
Source. Is usually used as an intermediate persistence mechanism.
Recordset Destination: Writes the records to an ADO record set.
SQL Server Destination: The destination that you use to write data to SQL Server most
efficiently.
SQL Server Compact Edition Destination: Inserts data into a SQL Server running on a Pocket PC.
Transformations
Transformations are key components within the Data Flow that allow changes to the data in the data
pipe. You can use transformations to split, divert, and remerge data in the data pipe. Data can also be
validated, cleansed, and rejected using specific rules. For example, you may want your dimension data
to be sorted and validated. This can be simply accomplished by dropping a Sort and a Lookup
Transformation onto the Data Flow design surface and configuring them.
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