Embedded analytics specialists for your dedicated team.

Where embedded analytics fits in a long-term product team.

Embedding is usually driven by adoption. Analytics in a separate tool with a separate login is used by a small fraction of the people who would benefit; the same charts inside the product are used by most of them.

Multi-tenant isolation is the hard requirement. A customer seeing another customer's data is a serious incident, and the isolation must be enforced at the data layer with authentication passed through correctly. This is security engineering, not report configuration.

What your dedicated team does with embedded analytics.

Performance expectations differ sharply from internal BI. An analyst tolerates a ten-second query; a customer inside a product does not, and slow embedded analytics reflects on the product.

Meeting that usually means pre-aggregation and caching designed in from the start, which is why the work is scoped with a dedicated data engineering team alongside the application capacity.

Common embedded analytics use cases.

• Analytics people use Insight inside the product, with no second login.
• Tenant isolation enforced at the data layer Access proven by testing, because a leak between customers is severe.
• Product-grade response times Pre-aggregation and caching designed in, because customers will not wait.

Adding embedded analytics skills to your team.

Embedded analytics is assigned across application and data capacity on one agreement, since isolation and performance sit on both sides of the boundary.

You can add embedded analytics capacity as one dedicated specialist or as part of a wider remote team, managed by a service delivery manager from our offices in Thailand. Companies hire dedicated developers this way under one agreement and one monthly fee.