Quasi-identifiers, or indirect identifiers, are personal attributes that are true about, but not necessarily unique, to an individual. Examples are one’s age or date of birth, race, salary, educational attainment, occupation, marital status and zip code.
There are times when it is necessary to test with or share data that has elements of personally identifiable information (PII). To comply with data privacy laws and prevent a data breach, you may need to provide data that reflects, and sometimes imparts, critical information, but still protects the PII.
This article focuses on IRI Workbench execution options for scripts based on the SortCL program language, which covers IRI Voracity ETL, CDC, SDC, pivoting and subsetting jobs, as well as its constituent product jobs; i.e.,