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For data architects

Keep architectural intent connected to implementation.

AnalyticsCreator connects business definitions, logical, physical and semantic models, transformation logic and implementation code in one governed project. Architectural decisions remain visible as the solution develops and supported target technologies change.

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Connected models. Visible implementation. Retained design knowledge.

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Model-Driven Architecture

Develop connected models. See their implementation.

Business, logical, physical and semantic models remain connected through their definitions, relationships and transformation logic.

Intelligent wizards work from source metadata and development choices to create project-specific structures and processing. The corresponding code evolves with the model and remains visible during development.

Native implementation assets and deployment packages are generated from this connected project for the selected supported environment. The project retains the design knowledge behind those assets.

Architecture Methods

Choose the architecture that fits the solution.

AnalyticsCreator supports established modelling methods and layered architectures. Optional customer-created templates or selected model elements can be reused where they fit the project.

Kimball
Dimensional modelling for reporting and analytics.
Data Vault 2.0
Historised integration and scalable change.
3NF / Inmon
Normalised structures for enterprise models.
Medallion
Bronze, Silver and Gold layers for ingestion, refinement and analytical use.
Hybrid designs
Combine approaches across staging, core, warehouse, datamart and semantic layers.
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Peter Smoly, CEO of Analytics Creator explains how to build a modern data warehouse new and changing requirements from business and IT result in a dificiency of your data architecture.

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Dependencies and Change

Assess changes in their architectural context.

Connected lineage exposes relationships between source structures, transformations and analytical models.

After source metadata is refreshed, affected places are automatically shown for new or changed source fields. Changes to business requirements are developed within the project, with its dependencies providing context for assessing the revised design.

Architecture Context for AI

Make recorded design knowledge available to AI.

Design Intelligence gives authorised MCP-compatible agents access to available saved-project definitions, relationships and confirmed dependencies.

This context supports explanations and technical proposals grounded in the project. Coverage limitations remain explicit, and explanations of why a decision was made depend on that rationale being recorded. Approval remains subject to the organisation's agreed controls.

Architecture Continuity

Adapt the technology. Retain the design knowledge.

Business definitions, relationships and transformation logic remain part of the project as supported target technologies evolve. Target-specific structures and settings can be adapted while building on the existing architectural foundation.

Technology changes can require design adjustments and validation. AnalyticsCreator retains the connected context for that work.

Data architecture: common questions

Which architecture methods does AnalyticsCreator support?

AnalyticsCreator supports Kimball dimensional modelling, Data Vault 2.0, 3NF/Inmon, Medallion and hybrid architectures. The project can combine approaches across its data and semantic layers.

Is AnalyticsCreator template-based?

No. Its intelligent wizards work from source metadata and development choices to create a project-specific model. Customer-created templates or selected model elements can be reused where appropriate, but a complete template is not required.

Can implementation code be inspected during modelling?

Yes. The corresponding code evolves with the model and remains visible during development. The project keeps model structures, relationships, transformation logic and implementation code connected.

What happens when a source field changes?

After source metadata is refreshed, AnalyticsCreator automatically shows affected places in the lineage for new or changed source fields. These dependencies provide context for assessing the design changes required.

Can AI agents access architectural context?

Authorised MCP-compatible agents can use Design Intelligence to query available saved-project definitions, relationships and confirmed dependencies. Coverage depends on the supported project information. Design rationale is available only where it has been recorded and exposed.