Business Requirements in Visual Basic .NET

Drawing QR Code in Visual Basic .NET Business Requirements

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Business Requirements
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than your test network, you can copy the deployment folder for your SSIS project to your production servers and then execute the manifest file to change the table names as required. To create a package deployment utility, open the solution that contains the SSIS project for which you want to create a package deployment in BIDS, right-click the project, and then choose Properties. In the Property Pages dialog box, select Deployment Utility as shown in Figure 9-3.
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Figure 9-3
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SSIS Deployment Utility.
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You can then configure the AllowConfigurationChanges and CreateDeploymentUtility properties and, optionally, update the location of the deployment utility by modifying the DeploymentOutputPath property. You then click OK, and in Solution Explorer you right-click the project and choose Build. When you have built the deployment utility, you can copy the collection of files to your target servers. To install the package on the target servers, you need to run the Package Installation Wizard. When you have verified that your SSIS package has installed correctly, you can use Microsoft SQL Server Agent to configure a schedule for package execution.
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Using Fuzzy Transformations
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Real-world data is dirty because of misspellings, truncations, missing or inserted tokens, null fields, unexpected abbreviations, and other irregularities. During the extract, transform, and load (ETL) phase, SQL Server 2005 cleans and standardizes new data and makes it consistent with existing data. The Fuzzy Lookup and Fuzzy Grouping transformations make the ETL process more resilient to common data
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Lesson 1: Enforcing Data Quality According to Business Requirements
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errors. They address matching and grouping problems without requiring complex, domain-specific rules and scripts.
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IMPORTANT
Fuzzy Grouping and Fuzzy Lookup transformations
Fuzzy Grouping and Fuzzy Lookup transformations are available only in the Enterprise version of SQL Server 2005.
Fuzzy Lookup lets you match records that users enter with clean, standardized records in a reference table. The matching process takes account of errors that are present in the input records. Fuzzy Lookup returns the closest match and indicates the quality of that match. Suppose, for example, customer information that a sales assistant enters during a new sales transaction does not match exactly with any record in the Customers reference table, which consists of all current customers, because of typographical or other errors in the input data. Fuzzy Lookup returns the best matching record from the Customers reference table and provides measures to indicate the match quality. Fuzzy Grouping enables you to identify groups of records in a table where each group potentially corresponds to the same real-world entity. Records in each group might not be identical but are very similar to each other. Fuzzy Grouping is used, for example, to group together all records in a Customers reference table that describe a single real customer. Fuzzy Lookup and Fuzzy Grouping use a custom, domain-independent distance function that takes into account the edit distance (for example, hits is distance 2 from bit ), the number of tokens, the token order, and relative frequencies. As a result, Fuzzy Lookup and Fuzzy Grouping achieve much finer discrimination than full-text searches because they capture a more detailed structure of the data. You can use Fuzzy Lookup and Fuzzy Grouping with little or no custom programming for ETL tasks in SQL Server 2005. Because they use more than just edit distance, Fuzzy Lookup and Fuzzy Grouping are not easily misled by transpositions and can detect higher level patterns than an approach that uses only edit distance.
The Fuzzy Lookup Transformation
Fuzzy Lookup can find data in large tables by using an incorrectly entered or incomplete string key. For example, if you want to look up customer information by name and address, you can use Fuzzy Lookup to find the information, even if your input does
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Business Requirements
not match exactly what is stored in your reference table. The Fuzzy Lookup transformation performs data cleaning tasks such as standardizing data, correcting data, and providing missing values.
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