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Data de-identification techniques in policy pushdown

When data protections that you use in policy pushdown enforcement include data de-identification techniques that aren't available in the source system, Data Governance and Catalog can replace the unavailable techniques with techniques of equivalent or stronger data anonymization.
The following table shows the data de-identification techniques that replace the techniques that aren't available in the source system:
Data Type
Data De-identification Technique Selected in Policy
Data De-identification Technique Applied in Source System
date
generalize date
generalize date
redact with null
redact with null
retain
retain
decimal
constant value
constant value
redact with null
redact with null
retain
retain
integer
constant value
constant value
redact with null
redact with null
retain
retain
tokenize consistently
constant value of "0" in Snowflake and Databricks
tokenize inconsistently
constant value of "0" in Snowflake and Databricks
string
constant value
constant value
generalize date
constant value of "XXX"
hashing in compatibility mode
hashing in compatibility mode in Snowflake and Databricks using MD5, SHA-1, SHA-256, and SHA-512 functions; constant value of "XXX" in Snowflake and Databricks using SHA3-256 and SHA3-512 functions
hashing in secret key mode
hashing in secret key mode in Snowflake using MD5, SHA-1, SHA-256, and SHA-512 functions; constant value "XXX" in Snowflake using SHA3-256 and SHA3-512 functions; constant value "XXX" in Databricks
redact with null
redact with null
retain
retain
substitute value consistently
hashing using SHA-256 in Snowflake; constant value "XXX" in Databricks
substitute value randomly
constant value "XXX" in Snowflake and Databricks
tokenize consistently
hashing in compatibility mode using SHA-256 in Snowflake; constant value "XXX" in Databricks
tokenize inconsistently
constant value "XXX" in Snowflake and Databricks
truncate
truncate
timestamp
generalize date
generalize date
redact with null
redact with null
retain
retain