Blueprint v1.0

Enterprise Data/AI Platform Blueprint

A modular architecture for scalable information engineering. Transform your fragmented data landscape into a unified, AI-ready platform that delivers measurable business value—layer by layer, module by module.

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25 Modules
5 Layers
Data Vault 2.0
Modular Data Platform Architecture Diagram - Sophisticated Technical Blueprint with Layered Integration

The Core Challenge: From Fragmented Data to Consistent Outcomes

Building a unified semantic platform that delivers reliable value—not once, but systematically

Data Flow Architecture: From Siloed Sources to Consistent Outcomes

The Challenge: Organizations struggle to create valuable outcomes from data sources trapped in silos—each with different formats, semantics, and quality levels.

The Solution: Centralized semantic processing in a secured platform that transforms fragmented data into consistent, trustworthy outcomes.

Three Types of Data Products

1. Data Governance Products

Quality control reports, compliance violations, data lineage, audit trails

2. Business Intelligence Products

Executive dashboards, operational reports, analytical APIs, KPI monitoring

3. AI Data Products

Intelligent agents, ready-to-use datasets, predictive models, automated insights

Critical Requirement: Cross-Product Consistency

AI answers must align with BI reports. Governance controls must validate both. Without a unified semantic foundation, organizations get conflicting insights—undermining trust and decision-making.

01

Why 95% of AI Projects Fail

The problem isn't AI technology—it's data chaos. Scattered silos, uncertain quality, and missing business context create a foundation too fragile for enterprise AI.

Scattered Data

Fragmented across silos, diverse sources, and legacy systems not designed to work together

Uncertain Quality

Siloed, inconsistent information undermines AI. In B2B, "mostly right" isn't good enough—you need 99.9% accuracy

Missing Context

No single source of truth. Without clean, integrated data and governance, even the best AI will fail

The Key Insight

AI Success = 95% Integration + 5% Inspiration

You need to integrate and govern data comprehensively so that AI systems have a trusted, single version of truth to reason over.

02

The Semantic Layer: AI's Missing Foundation

Data Vault 2.0 provides the architectural answer—an auditable corporate memory that creates a unified semantic layer, the single source of truth AI needs to deliver reliable results.

Four AI-Ready Benefits

Unified Semantic Model

All sources = one consistent view for AI reasoning

Full History by Default

Every change timestamped—"full data movie" for AI predictions

Quality & Compliance Built-In

Only verified data flows to AI/BI

Agile & Future-Proof

Add sources without breaking existing structures

Three Bidirectional Synergies

1. AI Accelerates Vault Creation

AI agents automate tedious tasks → Months of risky work → Days & risk-free

2. Vault Powers AI

Unified semantic layer + quality enforcement → Garbage In → Facts Out

3. AI Enriches Vault Data

AI outputs stored as governed assets → Insights → New data assets

The Virtuous Cycle

AI predictions are fed back into the system as governed data, transforming disposable insights into lasting informational capital. Organizations shift from firefighting data issues to innovating, from POC purgatory to production at scale.

03

The Data Paradox

Modern enterprises face a critical challenge: while data volumes grow exponentially, actual business value often stagnates. The root cause lies in architectural fragmentation and accumulated technical debt.

80-90%
of corporate data remains unstructured (emails, documents, audio, video)
10-20%
is structured in databases and SaaS solutions—yet most architectures target only this minority
Vast
organizational knowledge remains untapped due to legacy design limitations
04

5 Questions That Turn Data Into Value

Every component of the platform must answer five fundamental questions to ensure value creation and maintainability. This framework provides clarity and accountability across all architectural layers.

5 Core Questions of Data Architecture: How (Processes & Integration), What (Data Assets & Entities), Who (Roles & Governance), Why (Business Value & Strategic Goals), For Whom (Consumers & Requirements)
05

5 Embedded Layers Built Bottom-Up

The platform is structured in five progressive layers, from foundational infrastructure to strategic AI capabilities. Each layer builds on the previous one, ensuring stability and scalability.

Layer +2

Corporate Language Model

AI-driven innovation, semantic layer, and enterprise-wide intelligence

Modules 21-25
Layer +1

Transversal Integration

Cross-functional consistency, BI technologies, and data governance

Modules 16-20
Layer 0

Business Domains

Domain-specific data products delivering targeted business value

Modules 11-15
Layer -1

Data Foundations

Corporate image, transversal domains, business domains, and data quality frameworks

Modules 6-10
Layer -2

Infrastructure & Security

Data tech stack, infrastructure, security, risk management, and quality assurance

Modules 1-5
06

25 Modules: Modular Implementation

The blueprint consists of 25 discrete modules organized in a 5×5 matrix. Each module can be prioritized and deployed based on business needs, enabling incremental value delivery.

25 Modules Framework - Modular Enterprise Data/AI Platform Architecture (Layers +2 to -2)
07

beVault: Automation & Acceleration

AI-ready data in days, not months

beVault transforms Data Vault 2.0 from a methodology requiring extensive manual coding into an automated, metadata-driven platform that eliminates technical debt while accelerating delivery.

beVault Model-Driven Pipeline: Extract & Load, Store & Historicize, Verify & Enrich, Compose & Distribute, Orchestrate

DV2 Model Compliance

Build the model base don Hub, Links and Satellites fully compliant with DV standards due to VTCP certification by the data vault alliance

Built-In Quality

Embedded DQ module scans every record. Bad data quarantined, actions triggered—only certified information reaches AI/BI.

Smart Orchestration

Automated pipelines keep AI models and dashboards fed with latest data. Real-time to scheduled—all managed.

Rapid Integration from Silo's

Connect ERP, CRM, IoT, files, legacy DBs in clicks. Auto-maps to unified semantic model—no coding required.

Coherent Data Distribution

All AI, BI or data governance data products and outcomes are based on the same data an remain coherent on the long run.

AI, RAG Agentic & ML

Consistent, contextual data resolves hallucinations. Direct streaming to vector DBs & quality metadata.

BI & Analytics

Single source of truth for all reports, dashboards and APIs. AI answers match any other dashboards.

Data Foundations

Auto-populates data quality reports, data catalogs, lineage tracking, and compliance reports from Vault metadata ready to use for immediate data governance.

Low Switching Cost

Run on most of DBs and infra: + on-prem. Hybrid allowed

08

Evolutive and Layered Data Model

A flexible, multi-perspective architecture that seamlessly integrates structured and unstructured data across business domains while maintaining data quality and governance at every layer.

Evolutive and Layered Data Model: Domain and Holistic Perspectives with MDM at Core

D
Domain Perspective

  • Structured common data used across the enterprise
  • Domain-specific structured data tailored to business units
  • Cross-domain connexions enabling integrated analytics
  • Unstructured data integration (mails, docs, videos, audio, logs, reports)

H
Holistic Perspective

  • Master Data & central quality controls at the core
  • Business Domains & domain data quality in the middle layer
  • Transversal Domains for cross-functional integration
  • Enterprise-wide Business Language Model ensuring semantic consistency
09

Why dFakto?

25 years of proven expertise transforming enterprise data architectures into strategic assets

Certified Data Vault Excellence

First company worldwide to earn the Data Vault Alliance VTCP certification. Led by CEO Thibaut De Vylder, a long-time Data Vault 2.0 practitioner and recognized expert in the field.

Tooled Consulting Model

Operating like Palantir for enterprise data, we combine strategic consulting with powerful automation platforms (beVault, proPilot) to deliver concrete, measurable results—not just recommendations.

Battle-Tested Across Industries

Trusted by major enterprises in financial services, healthcare, manufacturing, and public sector. Our frameworks have been proven in the most demanding regulatory and operational environments.

25+
Years of Expertise

Founded in 1999, dFakto has been at the forefront of data platform innovation, evolving alongside the industry from data warehousing to AI-ready architectures.

70%
Faster deployment with beVault automation
Zero
Technical debt through metadata-driven approach

Business-Focused, Not Just Technical

We don't just build platforms—we ensure they deliver measurable business value. Every module answers: How? What? Who? Why? For whom?

Ready to transform your data architecture?

Contact Thibaut De Vylder, CEO • [email protected]+32 478 69 21 86

Visit dFakto.com
10

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