70-448 · Question #140
You are creating a SQL Server 2008 Integration Services (SSIS) package for Company.com. The package should contain a Data Flow task with a Fuzzy Grouping transformation that creates data. You should…
The correct answer is A. You should increase a Data Viewer object to the Data Flow task for constraints on the Fuzzy Grouping. Associates column values with a set of rows based on similarity, for data cleansing. SSIS Designer runs the package and provides detailed visual feedback about the pipeline. Depending on the size of the reference data, you may notice a delay while the error- tolerant index…
Question
You are creating a SQL Server 2008 Integration Services (SSIS) package for Company.com. The package should contain a Data Flow task with a Fuzzy Grouping transformation that creates data. You should browser the output data of the Fuzzy Grouping transformation to debug the package. Which is the correct answer?
Options
- AYou should increase a Data Viewer object to the Data Flow task for constraints on the Fuzzy Grouping
- BYou should increase a DBCC SHRINKFILE to the Data Flow task for constraints on the Fuzzy Grouping
- CYou should increase a web service to the Data Flow task for constraints on the Fuzzy Grouping
- DYou should increase a Transactions log to the Data Flow task for constraints on the Fuzzy Grouping
How the community answered
(14 responses)- A71% (10)
- B7% (1)
- C7% (1)
- D14% (2)
Explanation
Associates column values with a set of rows based on similarity, for data cleansing. SSIS Designer runs the package and provides detailed visual feedback about the pipeline. Depending on the size of the reference data, you may notice a delay while the error- tolerant index (ETI) is built. The ETI is the main data structure that Fuzzy Lookup uses at run time. After the ETI is built, all the input rows are processed and the results are written to the SSIS Designer gives you feedback about the progress of the pipeline by displaying the number of rows processed by each component. You can also place a Data Viewer on the pipeline by right-clicking the path between Fuzzy Lookup and the OLE DB destination. This allows you to visualize in real-time which rows Fuzzy Lookup has matched to your input rows. In addition to matching tuples, Fuzzy Lookup outputs a record-level similarity, individual column-level similarities, and a confidence score for each match result. For more information about these scores, see Interpreting the Results later in this paper.
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