Let AI Build Your BI
End-to-end analytics execution with LLMs, MCP, and Analytics-as-Code
Description
Most BI teams spend a lot of time just keeping things running. Metrics change, dashboards drift, and reports get rebuilt because no one is sure which version is right. Even small requests can turn into days of back-and-forth between data, BI, and business teams.
This paper looks at what changes when AI can work directly inside the analytics stack, rather than sitting on top of it.
It explains how GoodData uses large language models, Model Context Protocol (MCP), and analytics defined as code to let AI create and update metrics, run queries, and keep dashboards in sync, all within the same permissions and governance your team already uses.
Inside the paper:
- What it means for AI to execute analytics
- How MCP connects AI to semantic models, metrics, and dashboards
- How teams are using this approach to work through BI backlogs
- The kinds of speed and cost gains they’re seeing
- How to start with a single workflow and expand from there
Does GoodData look like the better fit?
Get a demo now and see for yourself. It’s commitment-free.
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