⚙️ elevata Platform Strategy¶
From SQL-Centric Pipelines to Metadata-Native Execution and Business Semantics¶
Document type: Strategy
Last updated: 2026-01
Applies since: elevata ≥ 0.8
🔧 1. Motivation¶
Modern data platforms increasingly rely on SQL-based transformation tools
to express not only technical data processing,
but also business logic, execution semantics, and governance intent.
This tight coupling leads to:
- implicit execution behavior
- limited explainability
- fragmented governance
- strong dependency on external orchestration and semantic layers
elevata addresses these limitations by treating metadata — not SQL — as the primary control plane for data platforms.
🔧 2. elevata Today¶
With the introduction of an explicit execution model, elevata has evolved beyond SQL generation into a platform execution core.
Key characteristics:
- deterministic execution planning
- explicit dependency graphs
- structured failure semantics (blocked vs aborted)
- batch-level execution identity (batch_run_id)
- execution snapshots and run-level observability
Execution is now:
- planned explicitly
- executed deterministically
- explainable independently of SQL rendering
SQL is an output artifact — not the orchestration mechanism.
🔧 3. Decoupling Business Logic from SQL¶
Traditional SQL-centric pipelines embed business meaning directly into SQL:
- calculations are implicit
- intent is inferred
- governance happens after execution
elevata separates concerns by making business intent explicit and declarative,
while keeping execution deterministic and warehouse-native.
🔧 4. Bizcore: Business Semantics without a Semantic Layer¶
Bizcore introduces a dedicated layer for business meaning.
It allows teams to define:
- business datasets
- business rules and classifications
- business calculations and KPIs expressed as dataset fields
These definitions are:
- metadata-driven
- deterministic
- compiled into execution plans
- independent of SQL dialects and BI tools
Bizcore is not:
- a BI semantic layer
- a metric store
- a query-time metrics engine
- a templating or macro system
Bizcore defines what data means — not how queries should behave.
🔧 5. Separation of Responsibilities¶
| Layer | Responsibility |
|---|---|
| RAW / STAGE / CORE | Technical correctness, historization, lineage |
| BIZCORE | Business meaning, rules, calculations |
| SERVING (optional) | Consumption- or tool-specific shaping |
This separation ensures:
- centralized business logic
- deterministic execution
- tool independence
- governance based on intent, not inference
🔧 6. Strategic Outcome¶
By combining:
- metadata-native execution
- explicit business semantics
- warehouse-native processing
elevata becomes a platform backbone, not a transformation tool.
External tools (orchestrators, BI platforms) integrate with elevata,
but do not define execution, semantics, or governance.
🔧 7. Long-Term Vision¶
elevata aims to become a metadata-native data platform engine:
a system where structure, execution, governance, and business intent
are derived from explicit definitions rather than implicit SQL behavior.
The goal is not to replace orchestration frameworks or BI tools,
but to provide a reliable, transparent core that makes data platforms
predictable, governable, and evolvable over time.