Gartner Framework

Data Fabric Architecture

A unified, intelligent layer that automates data integration, governance, and delivery across hybrid and multi-cloud environments

70%
Faster Delivery
50%
Cost Reduction
3x
Time to Insight
90%
Self-Service

WHAT IS IT?

Data Fabric is an architecture design concept that serves as an integrated layer of data and connecting processes. It uses continuous analytics over existing, discoverable, and inferenced metadata assets.

  • Unified data access layer across silos
  • Metadata-driven automation
  • Self-service data discovery
  • Intelligent data orchestration

WHY IS IT IMPORTANT?

Organizations struggle with data sprawl, silos, and integration complexity. Data Fabric addresses these by reducing integration design time by 30%, deployment by 30%, and maintenance by 70%.

  • 70% reduction in data delivery time
  • Eliminates manual integration coding
  • Enables real-time decision making
  • Future-proofs data architecture

HOW DOES IT WORK?

Data Fabric uses knowledge graphs and active metadata to automatically discover, profile, and catalog data. ML algorithms analyze usage patterns to recommend optimal integration paths.

  • Continuous metadata harvesting
  • ML-driven integration recommendations
  • Automated pipeline generation
  • Self-healing data workflows

Reference Architecture

End-to-end Data Fabric architecture with intelligent metadata layer

DATA SOURCES ACTIVE METADATA LAYER INTEGRATION ENGINE DATA PRODUCTS CONSUMPTION Databases Data Lakes SaaS Apps APIs IoT Streams Files Knowledge Graph Semantic relationships & lineage ML Recommendation Auto-suggest integrations Data Catalog Discovery & search Policy Engine Governance & security Data Virtualization Real-time federation ETL/ELT Pipelines Batch & streaming API Management Data services layer Event Streaming Kafka / Pub-Sub Customer 360 Product Financial Data Product Operations Data Product ML Features BI & Reporting Data Science Applications AI/ML Models External Partners

Core Components

01

Knowledge Graph

Catalog and document everything in the enterprise with relationships and semantic context.

  • Enterprise metadata catalog
  • Semantic relationship mapping
  • Business context integration
  • Automated discovery
02

Active Metadata

Leverage real-time metadata insights for intelligent data operations and automation.

  • Real-time metadata analysis
  • Automated classification
  • Usage pattern detection
  • Quality monitoring
03

Augmented Data Catalog

AI-powered catalog that continuously learns and improves data understanding.

  • ML-driven cataloging
  • Automated tagging
  • Smart recommendations
  • Natural language search
04

Embedded Data Integration

Seamlessly connect and integrate data from any source, anywhere in your ecosystem.

  • Universal connectors
  • Real-time streaming
  • Batch processing
  • API management
05

Orchestrated Data Pipeline

Automate and orchestrate complex data workflows with intelligent scheduling.

  • Visual pipeline builder
  • Dependency management
  • Error handling
  • Performance optimization
06

Governed Data Products

Deliver trusted, governed data products to consumers across the organization.

  • Data product lifecycle
  • Quality certification
  • Access governance
  • Usage analytics

How DaasLabs Implements Data Fabric

1

Assess & Discover

Catalog existing data assets, identify integration patterns, map business requirements

2

Design Architecture

Build knowledge graph, define semantic models, establish governance policies

3

Implement & Integrate

Deploy integration pipelines, enable active metadata, configure ML automation

4

Operationalize & Scale

Launch data products, enable self-service, monitor usage and continuously optimize

Ready to Build Your Data Fabric?

Schedule a consultation to discuss how Data Fabric architecture can transform your data landscape.