• 13 May 2025

Row Level Security in Amazon QuickSight

Understanding Row Level Security in Amazon QuickSight

Amazon QuickSight provides organizations with a practical way to enforce data access controls through Row Level Security (RLS). This feature enables dataset owners to restrict the visibility of specific data rows based on the user's identity accessing a dashboard or report. RLS is particularly essential in multi-tenant environments or business units that share a common reporting infrastructure but require strict separation of data visibility for privacy or compliance purposes.

Through RLS, QuickSight administrators can control which subset of data each user or group is authorized to view. This control is implemented by mapping users or groups to field values in a dedicated permissions dataset. When applied correctly, Row Level Security in Amazon QuickSight ensures that each user accesses only the data relevant to their role, department, region, or any other logical classification defined by the organization.

Rules and Behavior of Row-Level Security in Amazon QuickSight

In Amazon QuickSight, a permissions dataset is used to define which users or groups are allowed to see which rows of data. This dataset must not contain duplicate rows. If duplicate records exist, they are ignored when QuickSight evaluates which access rules to apply, which may result in unintended data exposure or restriction.

A typical configuration strategy involves including one column for user or group identifiers (such as email addresses or IAM roles) and one or more columns that match fields in the primary dataset, typically string-based columns like Region, Business Unit, or Customer Category. If an entry in the permissions dataset includes a user identifier with all other fields left null, that user is granted access to the entire dataset. On the other hand, if a user is not mentioned in the permissions file, they will not be able to view any data when accessing the report or dashboard.

It is also possible to implement a "deny" rule, which restricts users from viewing rows that match specific field values. In this configuration, users can only view data that does not correspond to the specified criteria. When RLS is enabled and active, the dataset within QuickSight is marked as "Restricted," signaling to administrators that access limitations are in effect.

A critical limitation of Row Level Security in Amazon QuickSight is that it only applies to string-based fields, such as varchar, char, or string data types. It does not support direct filtering using numeric or date fields. Organizations must plan around this constraint by creating derived fields or text equivalents of numerical categories where necessary.

Application and Practical Considerations

Implementing RLS typically involves two main steps: preparing a correctly structured permissions dataset and applying it to the target dataset within the QuickSight interface. For example, an organization that wants to limit sales data visibility by region might map each user's email to their respective sales region. When users log into QuickSight, they will only see the portion of the dataset that matches their assigned area.

Testing is a critical part of deploying Row Level Security. Administrators should verify user-specific views before releasing dashboards for broader use. This ensures that permissions are functioning correctly and that there are no unexpected gaps in data visibility due to misconfigured rules.

For organizations that maintain complex access structures, such as matrixed reporting lines or dynamic user groups, it may be necessary to refresh the permissions dataset regularly. Amazon QuickSight supports dynamic rules through SPICE and direct query datasets, but managing these effectively requires both planning and administrative oversight.

Expert Implementation Support from DataTerrain

DataTerrain has supported over 300 organizations in the United States with Amazon QuickSight configuration and deployment, including robust implementations of Row Level Security. Our team understands the intricacies of securing data visibility in high-scale environments and works closely with clients to align RLS configurations with organizational access policies.

We offer flexible engagement models without long-term contracts, allowing our clients to receive expert guidance precisely when they need it. Whether it involves creating permissions datasets, applying RLS configurations, or validating user-specific access, DataTerrain is positioned to assist organizations seeking reliable QuickSight implementations with clear, tested outcomes.