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...
The Master Data Services Configuration Manager can be used to do the initial setup and configuration of the MDS database and web application. The MDS Configuration Manager can be also used to upgrade the MDS database after a new SQL Server update has been installed or to repair the MDS database in case of corruption or configuration mismatch after a database has been restored from a backup. The Master Data Services Configuration Manager can also be used in migration scenarios, for example, when the MDS database needs to be moved to a different SQL Server instance or when to associate a different web application with an existing MDS database. In addition, the Master Data Services Configuration Manager is used to specify a series of system settings related to database and web application services. The main settings and setting categories include: General Settings Database connection time-out Database command time-out Web ser...
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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