In Integration Services, a source is the data flow component that makes data from different external data sources available to the other components in the data flow.
The source for a data flow typically has one regular output. The regular output contains output columns, which are columns the source adds to the data flow.
The regular output references external columns. An external column is a column in the source. For example, the MakeFlag column in the Product table of the AdventureWorks2008R2 database is an external column that can be added to the regular output. Metadata for external columns includes such information as the name, data type, and length of the source column.
An error output for a source contains the same columns as the regular output, and also contains two additional columns that provide information about errors. The Integration Services object model does not restrict the number of regular outputs and error outputs that sources can have. Most of the sources that Integration Services includes, except the Script component, have one regular output, and many of the sources have one error output. Custom sources can be coded to implement multiple regular outputs and error outputs.
All the output columns are available as input columns to the next data flow component in the data flow.
For more information, see Integration Services Sources.
The capabilities of transformations vary broadly. Transformations can perform tasks such as updating, summarizing, cleaning, merging, and distributing data.
The inputs and outputs of a transformation define the columns of incoming and outgoing data. Depending on the operation performed on the data, some transformations have a single input and multiple outputs, while other transformations have multiple inputs and a single output. Transformations can also include error outputs, which provide information about the error that occurred, together with the data that failed: for example, string data that could not be converted to an integer data type. The Integration Services object model does not restrict the number of inputs, regular outputs, and error outputs that transformations can contain. You can create custom transformations that implement any combination of multiple inputs, regular outputs, and error outputs.
The input of a transformation is defined as one or more input columns. Some Integration Services transformations can also refer to external columns as input. For example, the input to the OLE DB Command transformation includes external columns. An output column is a column that the transformation adds to the data flow. Both regular outputs and error outputs contain output columns. These output columns in turn act as input columns to the next component in the data flow, either another transformation or a destination.
For more information, see Integration Services Transformations.
A destination is the data flow component that writes the data from a data flow to a specific data store, or creates an in-memory dataset.
An Integration Services destination must have at least one input. The input contains input columns, which come from another data flow component. The input columns are mapped to columns in the destination.
Many destinations also have one error output. The error output for a destination contains output columns, which typically contain information about errors that occur when writing data to the destination data store. Errors occur for many different reasons. For example, a column may contain a null value, whereas the destination column cannot be set to null.
The Integration Services object model does not restrict the number of regular inputs and error outputs that destinations can have, and you can create custom destinations that implement multiple inputs and error outputs.
For more information, see Integration Services Destinations.
Joshua is working to become a Data Scientist with focus on Analytics, Big Data, Machine Learning, and Statistics. His passion for Data and Information are second to none. He is a certified IBM Cognos Expert with more than 10 years experience in Business Intelligence & Data Warehousing, Analtyics, IT Management, Software Engineering and Supply Chain Performance Management with Fortune 500 companies. He has specializations in Analytics, Mobile Reporting, Performance Management, and Business Analysis.
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