While ANO Work Tasks points to tables, ANO Rules point to columns. A Rule describes the logic of the anonymization of a specific column.
Three rule strategies
maskcreates new values for fields of a column using input sources
randomizeadds noise to the values of each field of a column
Shufflereorders values within a column, ensuring no value remains in its original place
If no input source is provided, the default input source becomes the masked column. E.g. it will be equal to using the column input source and referring to itself.
Convert the input source
The input source to the anonymization rule may be converted using
Output of a rule
The format of the output of a rule strategy can be formatted as needed.
transform the output
The output of the anonymization rule may be transformed using
Store the Anonymization to a Mapping File
To handle table dependencies during the anonymization process, such as foreign key constraints, you may want to propagate anonymizations of a primary key column to foreign key columns in other tables. Or you may want to populate a foreign key columns in child tables by using a distribution of primary key values available in parent tables.
unique keyword may be placed in a task rule to ensure the values stored in the database are unique. This may fail, depending on the input sources and sizes of tables. Not all input sources provide an infinite number of values. E.g.
random-integer is finite while
random-decimal is approximately infinite.
You can write complete SQL statements into the ANO file directly using
sql-after. This is useful if specific SQL statements must be executed before or after running a specific Task Group or a specific Work Task.
If there are needs to place conditions for Work Tasks, you may also write explicit
where expressions to them. These corresponds to the where clause of SQL statements.