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Use Cases

This guide provides practical examples of how to leverage the Decube Public API to automate common data management workflows and integrate with your existing systems.

User Management Automation

Automated User Onboarding

Scenario: Automatically create Decube users when new employees join your organization.

APIs Used: Control API - Users

  • POST /user - Create new users

  • GET /users - List existing users to avoid duplicates

Example Workflow:

  1. HR system triggers when new employee is added

  2. Check if user already exists using GET /users

  3. Create new user account using POST /user

  4. User receives welcome email with login instructions from Decube.

User Lifecycle Management

Scenario: Deactivate users when employees leave the organization.

APIs Used: Control API - Users

  • DELETE /user - Deactivate user accounts

  • GET /user - Verify user status before deactivation

Data Asset Discovery and Management

Automated Asset Catalog Updates

Scenario: Keep your data catalog synchronized with metadata changes from your data infrastructure.

APIs Used: Data API - Assets

  • POST /assets/search - Find existing assets

  • PATCH /assets - Update asset metadata and descriptions

  • GET /assets - Retrieve current asset details

Example Workflow:

  1. Data pipeline completion triggers metadata update

  2. Search for assets using POST /assets/search

  3. Update asset descriptions and ownership using PATCH /assets

Data Asset Discovery

Scenario: Build custom dashboards or integrations that surface relevant data assets to users.

APIs Used: Data API - Assets

  • POST /assets/search - Search assets by type, tags, or ownership

  • GET /assets - Get detailed asset information

Glossary Management

Automated Glossary Synchronization

Scenario: Maintain consistent business terminology across multiple systems.

APIs Used: Data API - Glossary

  • GET /catalog/glossary/list - List existing terms and categories

  • POST /catalog/glossary - Create new terms and categories

  • PATCH /catalog/glossary - Update existing definitions

  • POST /catalog/glossary/documentation - Attach documentation to terms

Example Workflow:

  1. Business stakeholders update terms in external system

  2. Sync process retrieves updated definitions

  3. Create or update glossary terms in Decube

  4. Attach rich documentation to terms

Data Lineage Tracking

Manual Lineage Documentation

Scenario: Document data transformations and dependencies that aren't automatically detected.

APIs Used: Data API - Lineage

  • POST /catalog/lineage/manual_lineage - Create lineage relationships

  • GET /catalog/lineage/manual_lineage - List existing lineage connections

  • DELETE /catalog/lineage/manual_lineage - Remove outdated lineage

Example Workflow:

  1. Data engineer completes new transformation pipeline

  2. Create manual lineage connections between source and target datasets

  3. Document the transformation logic in lineage metadata

  4. Update lineage when pipelines change

Access Control and Security

Group-Based Permission Management

Scenario: Automate user access provisioning based on organizational roles.

APIs Used: Data API - ACL Groups

  • GET /acl/group/list - List available groups

  • POST /acl/group/add_user - Add users to appropriate groups

  • POST /acl/group/remove_user - Remove users when roles change

  • GET /acl/group - Verify group memberships

Example Workflow:

  1. Employee role changes in internal system

  2. Determine appropriate Decube groups based on new role

  3. Add user to new groups and remove from old groups

  4. Verify permissions are correctly applied

Data Quality Reporting

Automated Data Quality Scorecard Generation

Scenario: Generate regular data quality reports for compliance and governance purposes.

APIs Used: Data API - Data Quality Scorecard

  • POST /data_quality_scores/report/generate - Request report generation

  • GET /data_quality_scores/report/result - Poll for report completion and download results

Use Cases:

  • Generate periodic data quality reports for compliance and governance

  • Export quality metrics for external dashboards and analytics

  • Track data quality trends over time across different data sources

  • Create automated alerts based on data quality thresholds

  • Audit data quality performance by data owner, schema, or asset type

Example Workflow:

  1. Scheduled job triggers data quality report request

  2. Submit request with desired filters (time range, data sources, dimensions)

  3. Receive job_id for tracking the asynchronous report generation

  4. Poll the results endpoint until report is ready

  5. Download the complete JSON report with quality scores and metrics

  6. Process results for dashboards, alerts, or compliance documentation

Monitors: Monitoring & Alerting Automation

Discover & Visualize Monitors

  1. A data catalog UI or external tool calls POST /monitors/search for a given asset.

  2. Show available scheduled and on‑demand monitors to users (name, type, incident level, last run status).

  3. Link into GET /monitors?monitor_id={id} to display the full configuration and recent execution summary.

Trigger On‑Demand Monitors after Upstream Change

  1. Upstream pipeline emits an event after data load/transform.

  2. Integration calls POST /monitors/trigger with the list of monitor ids or an asset identifier to run relevant monitors immediately.

  3. Poll GET /monitors/{monitor_id}/status to wait for completion.

  4. On completion, fetch details with GET /monitors/{monitor_id}/history and surface failures to downstream alerting or orchestration systems.

Temporarily Pause Scheduled Monitors for Maintenance

  1. Schedule maintenance window or detect noisy false positives.

  2. Call POST /monitors/enable-disable with { "monitor_id": <id>, "enabled": false } to disable the scheduled monitor.

  3. Re-enable when maintenance completes and verify the enabled flag via GET /monitors?monitor_id={id}.

Audit & Reporting

  1. Regular job calls POST /monitors/search to enumerate monitors for a tenant or team.

  2. For each monitor, call GET /monitors/{monitor_id}/history to collect run results and incident counts.

  3. Aggregate results into dashboards, compliance reports, or SLA measurement.

For more information, see:

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