# GoodData.AI vs Sigma for building customized dashboards based on individual user permissions?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Both <a class="a a--md" elv="true" href="https://www.g2.com/categories/embedded-business-intelligence">embedded business intelligence tools</a> come up constantly for customized dashboards, and they solve it in genuinely different places — which is the useful part of the comparison.</p><ol>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/gooddata-ai/reviews"><strong>GoodData.AI</strong></a> (4.3, 618 reviews) — Handles it in the analytics layer. Workspace label access control isolates each customer's data and enforces permissions based on who is logged in, which is why it comes up specifically for multi-tenant, customer-facing dashboards. Best when you're serving many external customers from one deployment and each must see only their own slice.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/sigma-computing-sigma/reviews"><strong>Sigma</strong></a> (4.4, 558 reviews) — Handles it in the warehouse. Every dashboard inherits row-level security and permissions already set in the cloud data warehouse, so access rules aren't rebuilt in the BI layer. Best when governance already lives in Snowflake or Databricks and you want one place to maintain it.</li>
</ol><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">That's the real decision: whether permissions should be defined once in the warehouse and inherited, or managed in the analytics platform where the tenancy model lives.</p><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Two adjacent options if neither shape fits:</p><ol>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/jaspersoft/reviews"><strong>Jaspersoft</strong></a> (4.1, 210 reviews) — Multi-tenant architecture giving each organization an isolated context, permission set, and report repository, with role mapping driven from SSO. Best when SSO groups are already your source of truth.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/ibm-cognos-analytics/reviews"><strong>IBM Cognos Analytics</strong></a> (4.1, 504 reviews) — Governed role-based access built for regulated, multi-department environments. Best where auditability matters more than embedding elegance.</li>
</ol><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">If you evaluated both for permissioned dashboards, what decided it — and did the warehouse-inherited model hold up when a customer asked for an exception?</p>

##### Post Metadata
- Posted at: 9 days ago
- Author title: Marketing Executive
- Net upvotes: 1


## Comments
### Comment 1

This distinction between analytics-layer and warehouse-level permissions is important. Sigma’s approach seems especially clean when governance is already mature in the warehouse, while GoodData.AI gives more flexibility when customer tenancy is managed within the analytics product. For teams that have used either model, how easy is it to handle one-off permission exceptions without creating governance headaches?

##### Comment Metadata
- Posted at: 6 days ago
- Author title: Writer





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