Investigate structured data in AI Data Engine
When database storage is growing unexpectedly, filter by table metadata to find which tables are oversized or have shown no activity since they were first discovered. For example, a storage administrator can identify large tables that haven't changed since an early scan, then coordinate with the database owner to evaluate whether they are still needed.
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At least one database data source must be connected and scanning. Refer to Connect a data source.
Review the database table listing
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From the AI Data Engine UI, select Investigation.
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Select the Structured tab.
The table displays database table name, schema, DB server, discovered time, table dimensions (columns × rows), and table size.
Identify oversized or unused tables
Use filters to narrow the listing to tables most likely to offer reclamation opportunities.
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Select Add filter, then select Discovered time.
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Set the range to surface tables that have been present across multiple scan cycles, for example tables first discovered more than a year ago.
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To narrow further, select Add filter again and filter by DB server or schema to focus on a specific system.
Applied filters appear as tags below the filter bar. The results update as you add each filter.
For a complete list of available filters, refer to Work with filters.
Review table details
Select a table row to open the detail panel and assess whether the table is a reclamation candidate.
The detail panel shows the DB server, schema, table dimensions, table size, and discovered time. Use this information to determine whether the table has grown since discovery or remains unchanged.
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Before acting on database tables, coordinate with the database owner to confirm the table is no longer needed. |
Save findings as a policy
After applying filters that identify tables of interest, save the criteria for ongoing monitoring.
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Select Create policy in the filter toolbar.
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Complete the policy form. Refer to Create a policy.
To download the filtered results from the Structured tab, select
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