データエンジニアリングに必要なすべてのツールを 機能パッケージとして標準統合

Visual, model-driven design from concept to production-ready code.

• Conceptual Data Modeling
• Logical Data Modeling
• Model Versioning

Define business metrics, hierarchies and relationships once — a governed semantic model that BI and AI tools consume consistently.

Generate output models automatically from rules — 3NF and Universal Star Schema are autogenerated through the API from the same business model, no hand-built dimensional layer required.

Talk to your data model and your data in plain language. Ask questions, explore relationships, and get answers — directly from the platform, no SQL required.

Batch, delta, CDC and near-real-time loads from any source — JDBC, files, NoSQL, streaming, or Python class.

Integrate data from multiple source systems into a unified Data Vault model with automated hub and link management.

Align inconsistent structures, naming conventions, and business keys across source systems without manual SQL.

Apply business rules, filter invalid records, and standardize values in the Business Vault layer — virtual or materialized. Business logic is defined as derivations, calculations and conformed rules in plain SQL, versioned with the model.

Generate output layers automatically from the same model — no rework, no duplicate pipelines.

• Dimensional Models (Star Schema)
• 3NF Models
• Data Products
• Flat Tables

Prepare structured, context-enriched data for machine learning and AI pipelines.

• Context-enriched Data

Explore and visualize your data directly in the platform — charts and dashboards with drill-down, no separate BI tool required.

Export any output to Excel — formatting, grouping and structure preserved — for ad-hoc sharing and offline analysis.

Profile source data, detect anomalies, and validate outputs. Full lineage from source to BI report. Test and validate your data in error marts and feed it back to your Data Steward.

Manage the metadata that keeps your data warehouse trustworthy and compliant.

• Data Ownership
• Data Domains
• Retention Periods

Every change captured and kept automatically — full, bi-temporal history you can reconstruct at any point in time.

• Automatic satellite historization
• Bi-temporal history (valid time + load time)
• Point-in-time and snapshot reconstruction

100% automatic lineage from every source table to every report column. REST API for Power BI, Tableau, and Qlik.

Every model, pipeline, and transformation is documented automatically — always up to date, always in sync with your actual data warehouse.

Deploy a model change to your own sandbox instantly and see the result on real data — before anyone else is affected.

Compare any two environments side by side and deploy exactly the differences you select — from development to test to production.

The complete implementation is versioned in your Git repository — every change traceable, reviewable and restorable.

• Gitflow support
• Full change history of model and code

Several engineers work on the same warehouse in parallel — each on their own model branch, merged back when the work is done.

• Model branching
• Model merging

Deployment scripts are generated automatically from the difference between two states — and executed by the platform, or handed to your own release process.

• Deployment script generation
• Deployment script execution
• Deployment APIs for CI/CD pipelines

Every deployment comes with its generated rollback script, so a release can be reverted as predictably as it was shipped.

Keep your pipelines running reliably without custom orchestration scripts.

• Load Orchestration
• Scheduling

Everything the GUI does is available through a REST API — model, deploy, orchestrate and govern entirely from code. Automate the full platform, integrate it into your own tooling, and script any workflow end to end.

Expose your data model and warehouse as an MCP server — ready for AI agents, copilots, and any tool that speaks the Model Context Protocol — across every stage of the warehouse.