Data locations

A data location is a database schema where successive model editions are deployed.

Data location types

The data location type is selected when the data location is created, and cannot be changed afterward.

There are two types of data locations:

  • Development data location: supports deploying both open and closed model editions. Suitable for testing models in development and quality assurance environments.

  • Production data location: supports deploying only closed model editions. Suitable for deploying data hubs in production environments.

Exercise caution when choosing the data location type, as it dictates which deployment operations can be performed. It is recommended to reserve production data locations exclusively for production and user-acceptance testing environments.

Content of a data location

A data location houses hub data, which is stored within the schema that is accessed via the data location’s datasource. This schema includes database tables and other objects generated from the model edition.

Three types of jobs (stored in the repository) can be carried out within a data location:

  • Installation jobs: for creating or modifying data structures in the schema non-destructively.

  • Integration jobs: for certifying data within the data structures based on model job definitions.

  • Purge jobs: for managing logs, data history, and deployment history according to retention policies.

In addition to the deployed model editions, jobs, and their execution logs, data locations also include configuration for:

  • Continuous loads, which integration specialists use to continuously push data into the data location.

  • Job notifications policies, which send notifications under specific conditions when integration jobs are completed, for administration, monitoring, or integration automation purposes.

  • Data notifications, used to propagate data from the data hub to downstream systems.

  • Data purge schedules, which reduce a data location’s storage volume by pruning the history of data changes and job logs.