06 Serving#
How data leaves the platform to be used: metrics defined once for every tool, dashboards and reports in BI tools, APIs for applications, results pushed into operational tools, tables shared with partners, fast stores for user-facing features, and AI agents that query data on people's behalf.
Before starting
02 Storage, 04 Modelling and transformation and 05 Governance and security, in particular Dimensional modelling, Authentication and authorization: OIDC and JWT and Row-level security and masking.
Pages, in reading order#
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A semantic layer defines business metrics, such as revenue or order count, together with the dimensions they can be grouped by and the joins between tables, once and in business terms, so that every tool that asks for a metric gets the same answer.
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2 Data APIs and the backend-for-frontend pattern
A data API serves platform data to applications through a defined HTTP interface instead of direct database access; a backend-for-frontend (BFF) is an API built for one specific application's screens.
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Sending results computed in the data platform, such as customer segments or scores, back into the operational tools where people and systems act on them: CRM, marketing, support and advertising platforms.
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4 Data sharing Optional
Giving another team or company read access to tables in place, through a sharing protocol or a catalog, instead of sending them exported copies.
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5 Low-latency serving stores Optional
Databases placed next to the lakehouse to answer queries in milliseconds for many concurrent users, kept in sync with the platform: real-time analytical databases for fast aggregates, and key-value stores for fast lookups.
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AI agents are language-model applications that answer questions and carry out tasks by calling tools; the Model Context Protocol (MCP) is an open standard for connecting agents to tools and data, including a data platform's catalog, semantic layer and query engine.
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Business intelligence (BI) tools let people explore data and build reports and dashboards; doing this well means choosing how the tool reaches the data, deciding who builds what, and designing dashboards for the decisions they support.