Every tool your data engineering team needs organized in functional packages

Datavault Builder includes multiple specialised tools in one platform — covering the full pipeline from data modeling and ingestion to delivery for analytics and AI. Built for data engineers who want to ship faster without the overhead of maintaining 9 separate products.

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  • 400% Productivity increase
  • 9 Tools replaced
  • 15 min Requirement to production
  • 100% Project Success

One platform. Every stage of your data warehouse.

Datavault Builder is not just a modeling tool — it includes a set of specialised tools, each covering a distinct task of data management, organized by the stage of the warehouse lifecycle it serves. Instead of assembling and maintaining 9 or more separate products, your team gets everything in one platform, ready to use.

Model

Design the warehouse with your business users — a visual model everyone can read, so definitions are agreed and communication improves before a line of code.

  1. Data Modeling

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

    • Conceptual Data Modeling
    • Logical Data Modeling
    • Model Versioning
    Conceptual model — business concepts and their relationships, grouped into subject areas.
    Detailed Data Vault model — hubs, links and satellites generated from the design.
  2. Semantic Model

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

    Define metrics, hierarchies and relationships once, consumed consistently by BI and AI.
  3. Rule-Based Output Models

    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.

  4. AI Data Modeling Agent

    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.

    Ask questions about your model and data in plain language — no SQL required.

Integrate

Consolidate every source into one integrated, enterprise-wide source of truth — a single, historized foundation, in the spirit of Bill Inmon.

  1. Data Ingestion

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

  2. Data Integration

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

    Multiple sources integrated into one Data Vault with automated hub and link management.
  3. Data Harmonization

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

    Harmonize structures, naming and business keys across systems into one consistent model.
  4. Data Cleansing

    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.

    Business logic defined in plain SQL in the Business Vault, versioned with the model.

Deliver

Prepare and shape the data exactly the way each consumer wants to see it — dimensional models, data products, flat tables and AI-ready sets.

  1. Data Delivery for Analytics

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

    • Dimensional Models (Star Schema)
    • 3NF Models
    • Data Products
    • Flat Tables
    Deliver analytics-ready output — here a stacked bar chart on the generated model.
  2. Data Delivery for AI

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

    • Context-enriched Data
    Context-enriched data ready for AI — explore it in plain language, no SQL required.
  3. Built-In Analytics

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

    Build charts directly on your warehouse data — here a pie-chart breakdown.
    Stacked bar charts and dashboards, with no separate BI tool.
  4. Excel Export

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

    Pivot and group your data interactively in the platform.
    Export the result to Excel with formatting and grouping preserved.

Govern

Keep the warehouse trustworthy — manage risk, control access, and fulfill obligations like GDPR, with built-in lineage and audit.

  1. Data Quality

    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.

    Define quality rules to profile, validate and test your data.
  2. Data Governance

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

    • Data Ownership
    • Data Domains
    • Retention Periods
  3. Data Historization

    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
  4. Data Lineage

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

    End-to-end lineage from every source column to every report field.
  5. Automated Documentation

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

    Always-current documentation generated automatically from the live warehouse.

Operate

Run, schedule and release reliably — orchestration and CI/CD built in, without custom scripts.

  1. Operations

    Keep your pipelines running reliably without custom orchestration scripts.

    • Load Orchestration
    • Scheduling
    Orchestrate and schedule loads visually — no custom scripts.
    Monitor every job run with detailed execution logs.
  2. CI / CD

    Enterprise-grade release management built into the platform — from development to production.

    • Direct Deployments
    • Git-flow based Versioning
    • Generation of Deployment Scripts
    • Generation of Rollback Scripts
    • Deployment APIs
    Compare and deploy changes across environments with Git-backed CI/CD.
  3. API Server

    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.

  4. MCP Server

    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.

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