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  1. Preface
  2. Data integration tasks
  3. Mapping tasks
  4. Data transfer tasks
  5. Data loader tasks

Tasks

Tasks

Rules and guidelines for data filters

Rules and guidelines for data filters

Use the following rules and guidelines for data filters:
  • When you create a data filter in a mapping in SQL ELT mode, use expression syntax that is valid in your cloud data warehouse. For more information, see the documentation for your cloud data warehouse. For other types of mappings, use Informatica transformation language expression syntax.
  • Data filters must contain valid SQL or SOQL operators.
  • You cannot include simple and advanced data filters in the same task.
  • When you convert a simple data filter to an advanced data filter, you cannot convert the advanced data filter back to a simple data filter.
  • A task fails if the fields included in the data filter no longer exist or if the data types of the fields change. If a data type changes, edit the task.
  • You can select Equals, Not Equals, Is Null, or Is Not Null operators on fields of the Other data type.
  • Applications do not apply filters with Equals, Starts With, or Ends With operators and string fields that contain data that starts or ends with a single quotation mark. To filter these records, use the Contains operator.
  • You can only use IS NULL and LIKE operators in data filters for fields of the Text, Ntext, and Image data types.
  • If you specify a date and no time for a date/time filter,
    Data Integration
    uses 00:00:00 (12:00:00 a.m.) as the time.
  • The list of available operators in a simple data filter depends on the data type of the field included in the data filter. Some operators do not apply to all fields included in data filters.
  • When you enter more than one simple data filter, applications filter rows that meet the requirements of all data filters.
  • When you use a parameter in a data filter, start the data filter with the parameter. For example, use $$Sales=100000 instead of 100000=$$Sales.

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