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Enable logging for package execution in SSIS

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Logging can be enabled and used at design time and runtime. To begin logging, in the Visual  Studio menu select SSIS > Logging to open the Configure SSIS Logs window. In  the Containers section, select the Control Flow objects for logging—the overall package itself  and/or each of the individual tasks within the package. Then in the Providers and Logs tab,  under the Add A New Log > Provider Type, select where you want the logging to be saved to,  and click the Add button: After adding each of the Provider Types selected you want to log to, go to the Select the  Logs to Use for the Container section to set up the Connection in the Configuration column.  In the case of a Text file, select a file to write to. For SQL Server DB as the target,  simply select the target database. You are not limited to selecting only one target location for  the logging, multiple destinations can be added and they will all be wri...
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Implement fuzzy grouping, fuzzy lookup with SSIS

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A frequent problem that you may experience when you bring data from multiple sources  that need to be unified and consolidated and/or needs to be deduplicated. In the case of an  enterprise maintaining multiple customer or product sales information in for various business  entities, e.g. retail and web sales, or possibly different CRM programs that are a result of  a company merger, all of this information has to be brought under one roof within the data  warehouse. SQL Server provides two fuzzy transformations to help with such scenarios: Fuzzy grouping Fuzzy lookup These transformations can be used independently or in concert to assist with unification  and deduplication of your data. Both the fuzzy transformation algorithms create and utilize  temporary tables created within SQL Server. Fuzzy grouping Fuzzy grouping is used primarily for deduplicating and standardizing values in column data. Fuzzy grouping has input parameters a...
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Non-blocking, semi-blocking, and blocking transforms in SSIS

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Not all Data Flow transforms are created equal. In fact, some are much faster and require a  lot less memory (non-blocking transforms). Others are slower while consuming much more  memory (blocking transforms), and some are in between (semi-blocking transforms). We don’t  always have a choice if we need to use a certain transform to do a certain specified task, but  it is good to know the differences between these types of transforms so that we can better  understand performance and resource utilization issues. Synchronous and asynchronous There is another related aspect about Data Flow transforms, which is their ability to quickly  process a row as they are coming into the transform, independently of any other rows that  came before or after (synchronous transforms). The other type of transform needs to be  dependent on some or all of the rows that come before and after (asynchronous transforms). On the whole, non-blocking transforms a...
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