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Data Masking Components: City Names Dynamic
{TOC}
"City Names Dynamic"
API Reference, CLR Reference (links)
Usage Instructions:
Purpose
The purpose of the component is to mask such values as Account or Patient Numbers that often consist of the combination of Alpha and Numeric characters and are not formed by a specific rule.
Algorithm
Variation of Random Character Permutation Algorithm
Description
 
City Name Dynamic component replaces letters with letters, while maintaining capitalization, and replaces numbers with numbers. It retains the non-alphanumeric characters, such as dashes, slashes, dots and comas, exactly at the position at which the non-alphanumeric characters presented themselves at the source value. It currently only replaces characters from alphabets that use English characters. The component will replace strings based on letters only with letter strings and strings based on numeric characters, only with numeric characters. For example, "Abc" will become "Zyx" and "123" will become "987" after component execution.
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Usage Instructions:
| 1. Configure a source that contains the column with alphabetical and numeric characters. The data in the column may also include any other character that will be treated as a separator. |
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2. Drag and Drop |
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3. Now, the precedence constraint (the blue arrow) passes proper meta-data to the |
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| 4. Now that the metadata for the GAN exists, and values are passed into the data masking component, please open the component editor: |
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5. In the second tab, there are input columns. Please check-mark only one column, the one that you will be masking with |
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| 6. This will create an extra column with the prefix “Masked_”. |
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| 7. Create a connection manager for the destination and configure source component for the destination. In the connection manager, in the tab “Mappings”, specify that you want newly created Field_Masked to be a field replacing the original value. For that, just click on the available input columns, choose the masked value, and map to the “Available Destination Columns” |
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8. Now, all the configurations are complete for the valid values.
You can run the package with the |
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Error Handling
| 9. If, however, there are invalid values in the package's source, one would need to configure error handling. Invalid values are those that are not conforming to the rules of the entity. To handle invalid values, each data masking component has error handling precedence constraint. One needs to create error destination connection and connect red arrow (error handling constraint) with this destination. As the connection is made, one needs to configure the state of failure: “Fail”,”Ignore” or “Redirect”. |
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10. It is recommended that one re-directs the output into the error destination, so that later one be able to analyze and process data for quality purposes. The |
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11. It is our suggestion that with |
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