Embedded Analytics: Should You Build or Buy?

Embedded analytics requires teams to choose between building a full business intelligence engine internally or purchasing a platform, with the decision shaped by budget, engineering capacity, timeline, security needs, and whether analytics is a core product differentiator. Building entails far more than charts, including query and caching infrastructure, tenant isolation, SSO, theming, dashboard editing, APIs, and compliance controls, along with ongoing maintenance and specialized expertise in areas such as row-level security, pre-aggregation, and audit readiness. It is most appropriate for internal-only tools, fixed and limited requirements, or organizations that already maintain dedicated BI teams. Buying shifts responsibility for BI infrastructure, optimization, visualization, and many security capabilities to a vendor, while the customer still owns warehouse connections, data-pipeline health, semantic metric definitions, and product integration. Buyers are advised to assess whether platforms use live warehouse data rather than extracts, provide meaningful end-user interactivity, and support governance requirements such as SOC 2, SSO, audit logs, and query-time tenant isolation. Sigma is presented as a warehouse-native embedded analytics platform that supports live governed data access, configurable embedding modes, role-based writeback, multitenant controls, and natural-language AI analytics.

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