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The goal of this document is to understand and implement the Global Address cleanse Transforms to Assess the quality of the Address data and to figure out the bad address data

Step 1: Create a New Job and add a Dataflow


Step 2: Inside the Dataflow, Select the source of address data from a table as shown below


Step 3: Select the Data Quality Transforms from the local object library pane and select the Global Address cleanse Transform i.e., UK_Address_Cleanse(Based on your address directory & licensing) as shown below


Step 4: Connect the Source data via Query Transform (if needed) and connect with UK_Address_cleanse Transform and then with the Target Table.


Step 5: Now open the Global Address Cleanse Transform and assign the Inbound attributes in the Input Editor as shown below.


Step 6: Goto the Options Tab and select the Address directory path and change the Generate Report data option as ‘YES’


Step 7: Go to Output Tab and select the 4 columns(Status Code, Info_Code, Quality_Code, Assignment Level) as shown below


Step 8: Save & Execute the Job. In the Execution properties, select the Export Data Quality Reports option.


Step 9: once the Job is executed, then log in to the Data Services Admin Console and click the Data Quality Reports


Now you can able to see your Job and corresponding Quality Reports got exported.


If you select the Quality Code Summary Report, this will show the Quality of your address data


Each Quality code implies different meaning

  1. Q2 :  Corrected Address
  2. Q3 : High likely that this address is deliverable
  3. Q4 : Fair likely that this address is deliverable
  4. Q6 : Highly Unlikely that this address is deliverable

And the below Summary chart shows the same.


You can click on each Quality code and drill down up to the record level for making further analysis and corrections.



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