EPAM Unified Data Platform Implementation for Microsoft Fabric

EPAM’s Unified Data Platform with Microsoft Fabric implementation helps enterprises consolidate disparate data sources into a scalable Unified Data Platform powered by Microsoft Fabric and a modern Data Lakehouse architecture.

This engagement is designed for CIOs, Chief Data Officers, enterprise architects, data platform teams, and analytics leaders who want to modernize legacy data environments, accelerate analytics delivery, and enable AI-ready data foundations. By implementing a unified Fabric-based architecture, organizations gain faster data access, improved reliability, reduced integration complexity, and governed analytics at scale.

Using Microsoft Fabric capabilities such as OneLake, Lakehouse architecture, integrated data engineering, and Power BI analytics, organizations can simplify their data architecture, enable near real-time insights, and build a strong foundation for AI, machine learning, and advanced analytics workloads.

What You Will Receive

• Microsoft Fabric Platform Setup: Deployment and configuration of Microsoft Fabric capacity with governance, monitoring, security controls, and integration with enterprise data sources.
• Unified Data Lakehouse Architecture: Implementation of a scalable Data Lakehouse using Microsoft Fabric and OneLake with medallion architecture (bronze, silver, gold) to organize raw, curated, and analytics-ready datasets.
• Data Platform Migration: Migration of data from legacy warehouses, fragmented storage platforms, or on-premises environments into a unified Fabric-based data platform.
• Data Pipeline Modernization: Transformation of ETL/ELT pipelines using Fabric data engineering capabilities to enable automated ingestion, transformation, and scalable data operations.
• Developer Productivity Integration: Integration of notebooks and data engineering workflows with Git-based version control to enable collaborative development and DevOps practices.
• AI-Ready Data Foundation: Enablement of machine learning and AI scenarios through MLflow integration, scalable analytics engines, and unified data access.
• Advanced Analytics Enablement: Implementation of semantic models and Power BI analytics leveraging Direct Lake for high-performance reporting and real-time insights.

Typical Implementation Approach

Phase 1 — Assessment

• Analyze the current data landscape including data sources, pipelines, storage systems, and analytics tools.
• Identify modernization opportunities and define a target-state Unified Data Platform architecture using Microsoft Fabric.
• Deliver a data platform assessment report and modernization roadmap.

Phase 2 — Planning

• Define the Fabric architecture including Data Lakehouse structure, governance model, and security policies.
• Create a migration strategy for data assets, pipelines, and analytics workloads.
• Develop an implementation plan covering integration, ingestion, transformation, and reporting.

Phase 3 — Proof of Concept

• Migrate selected datasets and pipelines to Microsoft Fabric.
• Validate lakehouse architecture, data ingestion pipelines, and analytics workloads.
• Confirm integrations with enterprise systems and analytics tools.

Phase 4 — Full Implementation

• Deploy Microsoft Fabric platform configuration and governance policies.
• Migrate production datasets and data pipelines to the unified platform.
• Implement lakehouse data layers, transformation pipelines, and Power BI semantic models.
• Deliver architecture documentation, operational runbooks, and governance guidelines.

Phase 5 — Support and Adoption

• Provide enablement sessions for data engineers, analysts, and platform teams.
• Establish operational governance and data management practices.
• Support teams during the transition to the Microsoft Fabric Unified Data Platform.

Expected Outcomes

• Up to 30% improvement in data reliability through unified data architecture and governed pipelines.
• Up to 55–70% cost optimization due to faster queries, optimized storage, and reduced I/O operations.
• Faster analytics and AI innovation enabled by a modern Data Lakehouse built on Microsoft Fabric.
• A scalable Unified Data Platform that serves as a trusted enterprise data foundation for analytics, reporting, and AI initiatives.