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Processing Objects Using Integration Services

Microsoft SQL Server Integration Services enables you to automate execution of DDL scripts, cube and mining model processing tasks, and data mining query tasks. Integration Services can be thought of as a collection of control flow and maintenance tasks, which can be linked to form sequential and parallel data processing jobs.

Integration Services is designed to perform data cleaning operations during data processing tasks, and to bring together data from different data sources. When working with cubes and mining models, Integration Services can transform non-numeric data to numeric data, and can ensure that data values fall within expected bounds, thus creating clean data from which to populate fact tables and dimensions.

There are two main elements in any Integration Services task or job: control flow elements and data flow elements. The control flow elements define the logical ordering of job progression by applying precedence constraints. The data flow elements concern connectivity between the output of a component to the input of the following component, plus any data transform that might operate on that data in between. As for the decision about where the data goes, precedence constraints contain logic to specify which component receives the output. The Integration Services tasks that are most relevant to Microsoft SQL Server Analysis Services include the Execute DDL Task, the Analysis Services Processing Task, and the Data Mining Query Task. For each of these tasks, the Send Mail Task can be used to send the administrator an e-mail message containing the task results.

The Execute DDL Task in Integration Services enables you to send DDL scripts directly to the Analysis Services server and to run them automatically. This allows the Analysis Services administrator to perform backup, restore, or sync operations from within an Integration Services package. A package is made up of the control and data flow elements described earlier, which all must be run regularly, as do other DDL statements that can be added to tasks. Because the tasks discussed here are frequently run at night, it is particularly useful to have packages that can easily be run from any scheduling application. You can schedule a package to be run at any time using Integration Services Agent. For more information about how to implement this task, see Analysis Services Execute DDL Task.

The Analysis Services Processing Task in Integration Services enables you to automatically populate cubes with new information when you make regular updates to your source relational database. You can process at the dimension, cube, or partition level using the Analysis Services Processing Task. The processing itself can be of type incremental or full, which you select based on your job requirements. Incremental processing adds new data and performs enough recalculation to keep the target up-to-date, whereas full processing drops existing data for a complete reload and recalculation. Full processing takes more time, but is more complete. For more information about how to implement this task, see Analysis Services Processing Task.

The Data Mining Query Task in Integration Services enables you to extract and store information from mining models. The information is often stored in a relational database and, for example, can be used to isolate a list of potential customers for a targeted marking campaign. Data mining can identify the value of a customer and the probability that the customer will respond to a particular marketing pitch. You can use the Data Mining Query Task to extract and modify data to a preferred format. For more information about how to implement this task, see Data Mining Query Task.

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