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Procedurally generated HR Data

By default, a demonstration set of HR data is imported into the MySQL database to hr.hr_people. SELECT access to this table is granted to the identityiq user. In the Compose and Swarm modes, this database is accessible as db.

All data is procedurally generated by a program developed at IDW. No record is intended to resemble any real-life individuals.

Description of the data

This data represents an imaginary medium-sized grocery store corporation.

The data has these properties:

  • There are around 8,500 full-time and part-time employees.
  • There are two affiliate companies (Primary Grocers Inc and Affiliate Grocers Inc) which have separate manager hierarchies and locations.
  • A few people may have a record at more than one company. For example, Jim worked as a cashier at Affiliate, then quit, then later took a job at Primary.
  • Rehire practices are perfect. Identities will have no more than one record per company.
  • The manager hierarchy is a consistent tree with multiple layers of managers depending on department size. Managers are mapped by employee number.
  • The full assortment of employment situations is represented: hired but not started, current employee, future end dates, terminated, rehired.
  • A small subset of users are current employees on leave (status L).

The employee_number field is intended as the unique ID.

Fake SSNs

The dataset includes an ssn field with SSN-formatted randomly generated values. These values begin with 9xx so are not valid SSNs. This field is intended for demonstrating or practicing PII management.

Additional datasets are available!

Arbitrarily larger or smaller randomly-generated HR data sets are available on request.

We also have generated higher ed identity datasets. These feature common higher-ed situations like:

  • Users coming from multiple simultaneous data sources (applicants, students, faculty, staff, alumni, contractors)
  • Users having different lifecycles per affiliation
  • Class and degree history
  • Decades of alumni
  • Affiliated hospital staff who may also be professors
  • Corrupted or mistaken data from some sources

University data sets can be as small as 4,000 identities or as large as several million.

Target database

A pair of provisioning target tables are also created in the MySQL database under the database target. These tables are defined in iiq-build/sql/target.sql. They are:

  • users: A table containing user details, such as username, first name, and last name. The table is pre-populated with a system administrator user called admin.
  • roles: A table containing roles, intended for use as entitlements. The roles are all pre-populated.
  • roles_users: A table joining users to the roles they are assigned.
  • roles_permissions: Associates roles (by name) with permissions. Each role can have more than one permission. The permissions are pre-populated. These can be used for playing with SOD policies.

Full CRUD access to these tables is granted to the identityiq user.