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  1. Preface
  2. Introduction to Accelerators
  3. Core Accelerator
  4. Data Domains Accelerator
  5. Australia/New Zealand Accelerator
  6. BCBS 239/CCAR Accelerator
  7. Brazil Accelerator
  8. Financial Services Accelerator
  9. France Accelerator
  10. Germany Accelerator
  11. India Accelerator
  12. Italy Accelerator
  13. Portugal Accelerator
  14. Spain Accelerator
  15. United Kingdom Accelerator
  16. U.S./Canada Accelerator

Accelerator Guide

Accelerator Guide

Australia/New Zealand General Data Cleansing Rules

Australia/New Zealand General Data Cleansing Rules

Use the general data cleansing rules to identify the type of information contained within input fields.
Find the general data cleansing rules in the following repository location:
[Informatica_DQ_Content]\Rules\General_Data_Cleansing
The following table describes the general data cleansing rules in the Australia/New Zealand accelerator:
Name
Description
rule_AUS_NZL_NER_Field_Identification
Identifies the type of information contained in an input field. The rule can identify names, Personal IDs, company names, dates, and address data from Australia and New Zealand. The rule returns a label that describes the type of input data. The rule uses probabilistic matching techniques to identify the types of information.

Dependencies on Core General Data Cleansing Rules

The Australia/New Zealand accelerator depends on the following general data cleansing rules from the Core accelerator:
  • rule_Assign_DQ_GeocodingStatus_Description
  • rule_Assign_DQ_Mailability_Score_Description
  • rule_Assign_DQ_Match_Code_Description
  • rule_Remove_Extra_Spaces
  • rule_Remove_Hyphen
  • rule_Remove_Leading_Zero
  • rule_Remove_Period_Parentheses
  • rule_Remove_Punctuation
  • rule_Remove_Punctuation_and_Space
  • rule_Remove_Space
  • rule_Replace_Limited_Punct_with_Space
  • rule_UpperCase
For more information about these rules, see Core General Data Cleansing Rules.

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