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A handy list with explanations of PACE terminology and concepts
A Schema is your data structure, i.e. the column headers and data type.
Principals are the way you authenticate to a data processing platform or catalog.
Data Policy
A Data Policy is the combination of schema and Rule Sets.
Data Contract
A data contract is another way to refer to PACE's data policy definitions.
Rule set
A Rule Set is a definition of how to treat a specific dataset to turn it into a dynamic view in a processing platform.
It includes:
  • Field Transforms, how to transform data (e.g. regex or nullify)
  • How to Filter data for a user based on conditions.
  • Access definitions (who can access the resulting view?)
Processing platform
A Processing Platform is commonly referred to as a data platform, like Snowflake, Databricks or Bigquery.
Data Catalog
A Data Catalog is your data shopping experience. For PACE, it's the source of the schema and global policies.
Global Transform
A global transform allows end-users to define field transforms once, and reuse them. An example is a tag based global transform, which allows to use tags that are set on specific fields in the respective processing platform, and translate them into default field transformations. An example could be personal identifiable information (PII) in specific columns of a table, that should be nullified when presenting data to arbitrary data consumers.