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11 changes: 9 additions & 2 deletions docs/content/product/auth/data-access-policies.mdx
Original file line number Diff line number Diff line change
Expand Up @@ -240,8 +240,15 @@ dimension in your query.

</WarningBox>

_When querying a view,_ data masking follows the same pattern as row-level
security: masking rules from both the view and relevant cubes are applied.
<WarningBox>

Unlike [member-level access policies][ref-dap-mls], which are **not** inherited
from cubes when querying through views, data masking rules **are** applied from
both the view and the relevant cubes. If you define masking on both a cube and a
view that uses that cube, the masking will be applied twice. To avoid unexpected
results, define masking rules on either the cube or the view, but not both.

</WarningBox>

For more details on available parameters, check out the
[`member_masking` reference][ref-ref-dap-masking].
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10 changes: 10 additions & 0 deletions docs/content/product/auth/member-level-security.mdx
Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,16 @@ Defining whether users have access to [cubes][ref-cubes] and [views][ref-views]
similar to defining access to database tables; defining whether they have access
to dimensions and measures — to columns.

<WarningBox>

Just like in many SQL databases where table-level column policies are not
inherited by views, member-level access policies defined on cubes are **not**
applied when querying through views. Only the member-level policies defined on
the view itself will take effect. Make sure to define access policies on your
views directly.

</WarningBox>

__By default, all cubes, views, and their members are *public*,__ meaning that they
can be accessed by any users and they are also visible during data model introspection.

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