Tutorial: Manage seismic analytics schedules and download reports

This tutorial demonstrates how to use the Seismic DDMS Analytics operation in Azure Data Manager for Energy to create recurring analytics schedules for your seismic data, list and download the generated reports, and delete schedules you no longer need. Scheduled analytics help you track storage consumption and data-access patterns across subprojects and tenants over time, so you can plan capacity and optimize storage costs without building a custom reporting pipeline. A background job computes the requested statistics on a recurring cadence and writes each report to Azure Blob Storage. You download report data directly from storage, and it never flows through the service.

In this tutorial, you learn how to:

Prerequisites

Before you begin, ensure you meet the following prerequisites:

• An Azure subscription.
• An Azure Data Manager for Energy resource with Seismic DDMS configured.
• A registered tenant and subproject in the Seismic DDMS service.
• The subproject.admin, datamanager, or tenant.admin role assigned to your user account, depending on the scope.
• A bearer token for API authentication. When you use DefaultAzureCredential, request the https://energy.azure.com/.default scope. See How to generate auth token.
• The data-partition-id of your tenant. A missing value returns 400 BAD_REQUEST.

Understand analytics scopes

Analytics jobs run at one of two scopes. The scope determines which datasets are measured and which role is required.

Each schedule stores three settings: the statistics to compute, the day of the week for the first run (first_execution), and how often it repeats in days (freq_execution). The API uses /job endpoints for schedule operations. A background job reads the schedules and writes reports to the sdms-analytics-reports container by using the path layout <subproject>/YYYY/MM/DD/.

Submit an analytics schedule

Submit a PUT request with a JSON array that contains a single schedule object. Omit name (or send an empty string) to create a tenant-wide schedule; provide a subproject name to scope the schedule to that subproject.

The request body supports the following fields:

1. Submit the request. For a subproject schedule, include the subproject name:

   PUT https://<instance>.energy.azure.com/seistore-svc/api/v3/analytics/job
   Authorization: Bearer {access_token}
   data-partition-id: {data_partition_id}
   Content-Type: application/json
   
   [
     {
       "name": "{subproject_name}",
       "statistics": "count,size",
       "first_execution": 1,
       "freq_execution": 7
     }
   ]
   

   For a tenant-wide schedule, omit name:

   PUT https://<instance>.energy.azure.com/seistore-svc/api/v3/analytics/job
   Authorization: Bearer {access_token}
   data-partition-id: {data_partition_id}
   Content-Type: application/json
   
   [
     {
       "statistics": "count,size",
       "freq_execution": 7
     }
   ]
   

2. Review the normalized schedule returned in the response. The type field is subproject for a subproject schedule and partition for a tenant-wide schedule. The first_execution field is returned as a timestamp for the next scheduled run:

   [
     {
       "name": "{subproject_name}",
       "type": "subproject",
       "statistics": "count,size",
       "first_execution": 1743552000000,
       "freq_execution": 7
     }
   ]
   

The service creates the recurring analytics schedule for the selected scope. Request only the statistics you need, and set freq_execution to match how often you consume reports.

Retrieve analytics schedules

Call the schedules endpoint to see the schedules you can view. Users with the tenant.admin or datamanager role get the complete list. A user with the subproject.admin role gets only the schedules for subprojects they can administer.

1. Submit the request.

   GET https://<instance>.energy.azure.com/seistore-svc/api/v3/analytics/job
   Authorization: Bearer {access_token}
   data-partition-id: {data_partition_id}
   

2. Review the returned schedules.

   [
     {
       "name": "{subproject_name}",
       "type": "subproject",
       "statistics": "count,size",
       "first_execution": 1743552000000,
       "freq_execution": 7
     }
   ]
   

The response contains the analytics schedules that your assigned role can view.

Retrieve generated reports

Reports become available after the first scheduled run completes. Retrieve reports for a single subproject or for the whole tenant, and optionally narrow the results by date.

The following query parameters control report-list and SAS URL requests:

1. To list reports for a subproject, call the subproject route:

   GET https://<instance>.energy.azure.com/seistore-svc/api/v3/analytics/job/{subprojectid}?filter-date=2026-09
   Authorization: Bearer {access_token}
   data-partition-id: {data_partition_id}
   

   To list reports for the whole tenant, call the tenant route:

   GET https://<instance>.energy.azure.com/seistore-svc/api/v3/analytics/tenant/job?filter-date=2026
   Authorization: Bearer {access_token}
   data-partition-id: {data_partition_id}
   

2. Review the list of report blob paths in the response:

   [
     "{subproject_name}/2026/09/15/{report_file_name}",
     "{subproject_name}/2026/09/22/{report_file_name}"
   ]
   

The response contains the report blob paths that match the selected scope and date filter. Use the most specific filter-date that meets your needs to reduce the number of returned paths.

Download a report with a SAS URL

Report data never flows through the service. Instead, request a short-lived SAS credential from the /connection-string endpoint, then use the returned SAS URL to read the report blobs directly from Azure Blob Storage. The filter-date you supply is appended to the storage path, so a more specific date scopes the credential to a narrower set of blobs. You can also use the extension parameter described in the preceding section to target an alternate reports container.

1. To request a SAS URL for a subproject report, call the subproject route:

   GET https://<instance>.energy.azure.com/seistore-svc/api/v3/analytics/job/{subprojectid}/connection-string?filter-date=2026-09-15
   Authorization: Bearer {access_token}
   data-partition-id: {data_partition_id}
   

   To request a SAS URL for a tenant report, call the tenant route:

   GET https://<instance>.energy.azure.com/seistore-svc/api/v3/analytics/tenant/job/connection-string?filter-date=2026-09
   Authorization: Bearer {access_token}
   data-partition-id: {data_partition_id}
   

2. Review the response. The access_token contains the SAS URL:

   {
     "access_token": "https://<account>.blob.core.windows.net/sdms-analytics-reports/...&sig=...",
     "expires_in": 3599,
     "token_type": "SasUrl"
   }
   

3. Use the SAS URL with the Azure Storage SDK or REST API to download the report path that you selected in the preceding section.

The returned SAS URL provides temporary access to the report blobs for the selected path and expires in just under one hour. Treat the URL as a secret: don't log or persist it, and request a new one after it expires.

Delete an analytics schedule

Delete an analytics schedule when you no longer want the service to generate recurring reports for that scope.

1. To delete a subproject schedule, call the subproject route:

   DELETE https://<instance>.energy.azure.com/seistore-svc/api/v3/analytics/job/{subprojectid}
   Authorization: Bearer {access_token}
   data-partition-id: {data_partition_id}
   

   To delete a tenant schedule, call the tenant route:

   DELETE https://<instance>.energy.azure.com/seistore-svc/api/v3/analytics/tenant/job
   Authorization: Bearer {access_token}
   data-partition-id: {data_partition_id}
   

2. Confirm that the request returns 200 OK. Deleting a schedule that doesn't exist also succeeds, so the operation is safe to retry.

The analytics schedule is deleted, and the service no longer generates recurring reports for that scope.

Clean up resources

This tutorial doesn't provision a new Azure resource. To stop future reports from being generated, delete the analytics schedule as described in Delete an analytics schedule.

Related content

• Tutorial: Work with seismic data by using Seismic DDMS APIs
• How to generate auth token
• Seismic DDMS API reference