Staging Processing
Staging Tables are compatible with any type of Program; that is, you can map a Program target Table Descriptor of any type—Staging, Reload, or Transactional—to a staging Table instance.
Staging processing is designed specifically to hold data only for the duration of the execution of the Program or Load Set that writes to the Table instance. If the Program to which a staging Table instance is mapped is contained in a Report Set of Workflow, the system retains the data for the duration of the master job (the whole Report Set or Workflow). However, you can choose to audit a staging Table instance, so that its data is never hard-deleted:
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Staging with Audit. In staging processing with auditing, the system does not delete any data; the records remain in the table with a creation timestamp equal to the refresh timestamp of the job that inserted them. The staging processing logic allows a job to process only records whose creation timestamp is equal to its own timestamp. Records in a staging Table instance do not have an end timestamp.
There is no relationship between records with one creation timestamp and those with another, whether or not they share a unique or primary key. For example, loading the same set of records twice will result in the table containing two complete sets of the loaded records.
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Staging without Audit In staging processing without auditing, immediately before the next execution of the Program, the system hard-deletes the data in the table. This setting saves space in the database.
More than one job can run on a staging table instance at a time. Each job can "see" only the records whose creation timestamp is equal to its own refresh timestamp.
Example: You might want to audit data in a staging table that you use for reports on different subsets of data; for example, a Table that holds Adverse Events data that you report in groups according to patient age: one report for Patients in their 20s, another for those in their 30s, and so on.
Parent topic: Data Processing Types