Release Security Dataset

The Release Security dataset enforces row-level security on dashboards by filtering release data based on your login credentials. This ensures that you can only view the release folders you are authorized to access. By linking your identifiers to relevant records, the dataset helps maintain data integrity and supports controlled access to sensitive or role-based release information.

note

This dataset excludes records where the release folder is marked as soft deleted. Only active folders are included.

Dataset Components

The following table describes the key attributes of the Release Security dataset:

Attribute Name	Description
Security flag	Indicates whether row-level security is applied. Default value: 'Y'.
Security hash	Identifies the release folder you have access to.
Sys_source	Unique identifier of the source.

note

This dataset does not include any metrics.

Implementing Row-Level Security

This section explains how to use the Release Security dataset to implement row-level data security in dashboards. It provides steps and examples for common use cases.

Datasets Enabled for Row-Level Security

The following datasets are enabled for row-based data security:

1. Release folder hierarchy
2. Release security dataset 1
3. Release security dataset 2
4. Release security dataset 3
5. Release security dataset 4
6. Release security dataset 5

All other datasets in Release are cached by default and do not support row-level security.

These datasets are used to implement security in your dashboard. If the dashboard includes multiple types of analysis such as release, dependent, and dependency, you may need to use a separate security dataset for each type. Workflow analysis is not part of self-service but is secured by default.

Steps to Enable Row-Level Data Security for Additional Datasets

To apply row-level security to dashboards using non-secured datasets, follow these steps:

1. Add Datasets: Include both security-enabled and non-secured datasets in the dashboard.
   • Example: Release folder hierarchy (secured) and Release analysis (not secured).
2. Blend Datasets: Blend the datasets using the Child folder ID attribute (from Release folder hierarchy) and the Release folder ID attribute (from Release analysis).
3. Apply Security Flag: Add the Security flag field from the security-enabled dataset as a global filter and set its value to 'Y'.

Global Filter Settings

• Enable "Disable interactions in the library."
• Disable "Show for all options."
• Disable "Allow multiple selections."
• Set "Display Style" to Drop-down.

If your dashboard contains multiple independent datasets, repeat these steps for each dataset.

Use Case Examples

Use Case 1: Basic Hierarchical Security

Scenario: Apply hierarchical security to a dataset that is not secured by default.

Datasets Used:

• Release folder hierarchy (secured)
• Release analysis (not secured)

Steps:

1. Right-click the Child folder ID attribute, select Link to Other Dataset, and choose the Release folder ID attribute from the Release analysis dataset.
2. On the View menu, select Filter Panel.
3. Select the ellipsis (…), point to Add Filters, select Security flag, and click OK.

The dashboard will display only data for release folders the user is authorized to view.

Use Case 2: Securing Without Using Folder Hierarchy

Scenario: Apply security without requiring hierarchical analysis.

Datasets Used:

• Release security dataset 1 (secured)
• Release analysis (not secured)

Steps:

1. Right-click the Release folder ID attribute, select Link to Other Dataset, and choose the Security hash attribute from the Release Security dataset 1.
2. On the View menu, select Filter Panel.
3. Select the ellipsis (…), point to Add Filters, select Security flag, and click **OK`. Set the filter to 'Y'.

Use Case 3: Securing Multiple Independent Datasets

Scenario: Secure multiple datasets with individual configurations.

Datasets Used:

• Release security dataset 1 (secured)
• Release security dataset 2 (secured)
• Release dependent analysis (not secured)
• Release dependency analysis (not secured)

Steps:

1. In the Release dependent analysis dataset, right-click the Release folder ID attribute, select Link to Other Dataset, and choose the Security hash attribute from the Release Security dataset 1.
2. On the View menu, select Filter Panel.
3. Select the ellipsis (…), point to Add Filters, select Security flag, and click **OK`. Set the filter to 'Y'.
4. In the Release dependency analysis dataset, right-click the Release folder ID attribute, select Link to Other Dataset, and choose the Security hash attribute from the Release Security dataset 2.
5. Repeat steps 2–3 for the second dataset.

The dashboard will enforce row-level access controls for both datasets independently.

Use Case 4: Securing Dataset Without Folder ID

Scenario 1: Apply security to a custom dataset.

Datasets:

• Release security dataset 1 (secured)
• Custom dataset 1 (not secured)

Steps:

1. Ensure the Release folder ID column is included in the custom dataset and publish it.
2. Right-click the Release folder ID attribute, select Link to Other Dataset, and choose the Security hash attribute from the Release Security dataset 1.
3. On the View menu, select Filter Panel.
4. Select the ellipsis (…), point to Add Filters, select Security flag, and click **OK`.

Scenario 2: Apply security using the Release folder hierarchy.

Datasets Used:

• Release folder hierarchy (secured)
• Custom dataset 2 (not secured)

Steps:

1. Ensure the Release folder ID column is included in the custom dataset and publish it.
2. Right-click the Release folder ID attribute, select Link to Other Dataset, and choose the Child folder ID attribute from the Release folder hierarchy dataset.
3. On the View menu, select Filter Panel.
4. Select the ellipsis (…), point to Add Filters, select Security flag, and click **OK`.

By following these steps, you can implement robust row-level security for your dashboards, ensuring controlled access to sensitive data.