Using external reporting and OLAP tools, query the datamart directly and generate reports. The database schema diagrams provide the means to create advanced query scripts to extract required information from the datamart.
Save a copy of your TeamForge site's data to a location from where you can quickly retrieve it to your TeamForge site.
The ability to run separate PostgreSQL instances for TeamForge database and datamart on the same server has been deprecated in TeamForge 17.11.
You can customize your reports by modifying the parameters in config.ini file. For example, some reports require a particular data source such as datamart and some require a particular license type such as ALM.
The etl-client.py script allows you to access the Extract, Transform and Load (ETL) scheduler and check the status of the jobs configured. The script also supports triggering jobs manually.
These are some of the frequently asked questions on TeamForge database, datamart, ETL, PostgreSQL, Oracle and so on.
You can install TeamForge with its database installed separately on an external PostgreSQL server such as AWS RDS/Aurora.
The psql-reporting-wrapper script is used to connect to the datamart.
Generate a report to get a snapshot of what is going on in a project. You can generate reports on data stored in both TeamForge's production (operational) database or datamart. Datamart, also known as the Reporting database, is build by extracting, transforming and loading (ETL) TeamForge's production data to a separate database (datamart) at regular intervals.
Set the interval at which you want yourTeamForge site's data extracted to the datamart from which reports are generated.
TeamForge ETL jobs can extract transform and load the TeamForge tracker association data to the datamart for reporting purposes.