Migrate to Microsoft Fabric

Modern enterprises often run a convoluted patchwork of analytical tools: Azure Data Factory for ETL, Azure Synapse or Databricks for compute, dedicated SQL data warehouses for relational queries, and dozens of disconnected Power BI workspaces refreshing multi-gigabyte import datasets every night. This fragmented architecture leads to rampant data duplication, massive cloud storage and egress bills, synchronization delays, and constant governance headaches.

Microsoft Fabric fundamentally transforms enterprise data architecture. Built around OneLake—the "OneDrive for data"—Fabric standardizes all storage on open Delta Parquet format. With revolutionary Direct Lake mode, Power BI semantic models read directly from OneLake storage at in-memory speeds without importing data or running slow DirectQuery SQL translations. Compute resources are unified under flexible Fabric Capacities (F-SKUs), allowing organizations to rightsize spending across workloads.

Codersarts provides end-to-end Microsoft Fabric migration consulting. We audit your existing Azure or on-premise estate, architect a clean medallion Lakehouse, migrate ETL pipelines and notebooks, configure zero-copy OneLake shortcuts, and unlock instant Direct Lake reporting for your executive teams.

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Is This You?

Enterprise data leaders and engineers regularly encounter painful architectural roadblocks:

• "We are paying for multiple redundant cloud services across ADF, Synapse, and Power BI Premium."

  
  

  You manage separate billing meters and idle compute clusters across Azure; you need to consolidate onto unified Fabric Capacity (F-SKUs) to optimize total cost of ownership.

• "Our Power BI scheduled refreshes take hours and constantly duplicate warehouse data."

  
  

  Every dataset import creates another copy of your data; you need Direct Lake mode so Power BI visualizes Delta tables in OneLake directly with zero refresh delays.

• "Our data sits in silos across AWS S3, Google Cloud, Snowflake, and Azure Data Lake."

  
  

  Copying data across clouds causes latency and egress fees; you need OneLake Shortcuts to virtualize external buckets into a single unified Fabric namespace without moving data.

• "We have legacy SSIS packages or complex Azure Data Factory pipelines that need modernization."

  
  

  Your data pipelines are fragile and expensive to maintain; you need to migrate to Fabric Data Factory pipelines and native PySpark notebooks.

• "We want to implement the Medallion Lakehouse architecture (Bronze, Silver, Gold) in Fabric."

  
  

  You need a standardized data engineering pattern that ingests raw data (Bronze), cleans and deduplicates it (Silver), and aggregates it into dimensional models (Gold).

• "Our team is unsure whether to use Fabric Lakehouses, Fabric Warehouses, or Eventhouses."

  
  

  You need certified enterprise data architects to design the optimal workload split between Spark-driven Lakehouses, T-SQL Warehouses, and real-time streaming Eventhouses.

The Cost of Inaction: Maintaining legacy data silos leads to spiraling cloud infrastructure bills, delayed reporting cycles, vendor lock-in, and an inability to support modern generative AI and Copilot workloads.

What Professional Microsoft Fabric Migration Delivers

A modern, consolidated lakehouse platform built for scale, governance, and speed:

• Zero Data Duplication with OneLake: Single unified storage layer where all compute engines (Spark, SQL, Power BI) query the same Delta Parquet files.

• Instant Direct Lake Reporting: Sub-second Power BI visual queries reading directly from OneLake Delta tables with zero data movement and zero scheduled refresh latency.

• Virtual Multi-Cloud Unification: Connect Amazon S3, Google Cloud Storage, and Snowflake using OneLake Shortcuts without incurring data migration costs.

• Consolidated Cloud Compute (F-SKU): Dynamic auto-pause and smoothing across unified Fabric capacity, slashing overall licensing costs.

• Medallion Lakehouse Standardization: Robust, automated PySpark pipelines processing Bronze (raw), Silver (cleansed), and Gold (curated) analytical layers.

• Enterprise Security & Governance: Centralized Purview integration, OneSecurity row-level protections, and automated deployment pipelines (Dev/Test/Prod).

Our Microsoft Fabric Migration Services

We provide complete, lifecycle migration consulting from initial workload discovery to production deployment:

1. Architecture Assessment, Fabric Capacity Planning & Sizing

• Auditing existing data estate: Azure Synapse, Azure Data Factory, Databricks, SQL Server, Snowflake, and Power BI Premium capacities.

• Fabric Capacity sizing analysis: mapping current peak compute requirements to optimal Fabric F-SKUs (F64, F128, etc.) with burst smoothing.

• Defining the multi-workspace topology and environment separation strategy (Development, UAT, Production).

• Establishing a risk-mitigated phased migration roadmap with zero downtime for downstream operational reporting.

2. OneLake Architecture & Medallion Lakehouse Engineering

• Structuring the OneLake lakehouse hierarchy using the industry-standard Medallion Architecture:

o Bronze Layer: Raw data ingestion preserving source schemas, history, and timestamps.

o Silver Layer: Cleansed, validated, and conformed Delta Lake tables with schema enforcement.

o Gold Layer: Optimized star schema dimensional models (Fact and Dimension tables) ready for business consumption.

• Configuring OneLake Shortcuts to virtualize data lakes in Azure Data Lake Storage Gen2 (ADLS Gen2), Amazon S3, and Google Cloud Storage without physical copying.

3. Pipeline & Notebook Migration to Fabric Data Factory

• Converting Azure Data Factory (ADF) pipelines and legacy SSIS packages into modern Fabric Data Pipelines and Dataflows Gen2.

• Migrating Synapse Spark and Databricks notebooks into native Fabric PySpark Notebooks with Delta Lake ACID transaction optimizations.

• Implementing automated data compaction (OPTIMIZE and V-Order) to maximize Delta Parquet compression and Direct Lake query performance.

• Setting up automated error handling, retry policies, and alert monitoring via Fabric workspace notifications.

4. Fabric Warehouse & T-SQL Analytical Layer

• Migrating Synapse Dedicated SQL Pools and on-premises SQL data warehouses into high-performance Fabric Data Warehouses.

• Optimizing T-SQL schemas, data types, and primary/foreign key metadata constraints to maximize engine query plans.

• Enabling cross-database querying between Fabric Lakehouses and Fabric Warehouses within the same OneLake boundary.

• Structuring granular security: Object-Level Security (OLS), Column-Level Security (CLS), and Dynamic Row-Level Security (RLS).

5. Direct Lake Mode Power BI Modeling & Semantic Layer

• Converting traditional Power BI Import and DirectQuery models into revolutionary Direct Lake mode.

• Ensuring Delta tables strictly adhere to Direct Lake constraints (V-Order sorting, supported data types) to prevent fallback to DirectQuery.

• Engineering enterprise semantic models directly on Gold Lakehouse Delta tables using Tabular Editor and Power BI Desktop.

• Eliminating scheduled refresh schedules: downstream dashboards reflect newly ingested data within seconds of lakehouse commit.

6. Governance, Microsoft Purview & CI/CD Deployment

• Configuring end-to-end data lineage, automated metadata scanning, and enterprise cataloging via Microsoft Purview.

• Implementing Fabric Git integration with Azure DevOps or GitHub for automated version control across notebooks, pipelines, and reports.

• Setting up Fabric Deployment Pipelines to govern automated code promotion across Development, Test, and Production workspaces.

• Establishing cost governance dashboards to monitor Capacity Unit (CU) consumption and prevent capacity throttling.

Common Use Cases We Build For

Our Microsoft Fabric migration solutions modernize data estates across industries:

• Azure Synapse to Fabric Lakehouse Migration: Transition deprecated Synapse dedicated and serverless pools to Fabric Lakehouses and Warehouses.

• Azure Data Factory & SSIS Pipeline Modernization: Replace tangled on-premise SSIS and cloud ADF orchestrations with unified Fabric pipelines.

• Enterprise Power BI Consolidation into Direct Lake: Eliminate gigabytes of redundant Power BI dataset imports by switching to sub-second Direct Lake reporting.

• Multi-Cloud Data Unification via OneLake Shortcuts: Query distributed AWS S3 and GCP data lakes alongside Azure datasets without data movement.

• Real-Time Telemetry & Eventhouse Analytics: Stream IoT sensor and clickstream logs into Fabric Real-Time Intelligence Eventhouses for live alerting.

• Fabric Capacity Rightsizing & Cost Optimization: Consolidate disparate compute licensing into a single rightsized F-SKU with automated auto-pause.

What You Get (Deliverables)

Every Codersarts Microsoft Fabric migration engagement delivers a complete, production-ready enterprise lakehouse:

• Production-Ready Fabric Workspace Architecture: Fully configured Dev/Test/Prod workspaces with integrated OneLake security and deployment pipelines.

• Validated Medallion Lakehouse (Bronze, Silver, Gold): Structured Delta Parquet tables with automated ingestion, schema validation, and compaction routines.

• Migrated Pipelines & Fabric PySpark Notebooks: Complete, documented ETL codebase executing reliable scheduled and event-driven data workflows.

• High-Performance Direct Lake Semantic Models: Certified Power BI models querying OneLake directly with verified sub-second rendering.

• OneLake Shortcuts & Multi-Cloud Connectivity: Configured zero-copy shortcuts connecting external cloud storage buckets.

• Data Lineage & Purview Governance Catalog: Mapped asset catalog with sensitivity labels and end-to-end data lineage tracking.

• Fabric Capacity & Cost Management Playbook: Documentation detailing Capacity Unit monitoring, pause/resume rules, and workload optimization.

• 60-Minute Administrative & Developer Handover: Live recorded training walking your internal data engineering team through maintenance and ongoing development.

What We Need From You

To begin planning and executing your Microsoft Fabric migration, we require:

• Current Architecture Schematics: Documentation or architectural diagrams of your existing databases, ETL pipelines, and reporting tools.

• Source Data & Cloud Access: Access to current Azure subscriptions, AWS/GCP buckets, database instances, or Power BI tenants.

• Target Data Workloads & Sizing: Estimates of historical data volume, daily ingestion rates, peak user concurrency, and query latency SLAs.

• Security & Compliance Requirements: Enterprise governance mandates (HIPAA, GDPR, SOC 2), data residency rules, and role-based access requirements.

• Microsoft Fabric Licensing Status: Existing Fabric Capacity (F-SKU) or Power BI Premium Capacity (P-SKU) details.

How It Works: Our 5-Step Fabric Migration Process

We take enterprise data platforms from fragmented silos to unified Fabric lakehouses through a proven 5-step methodology:

• Step 1: Estate Discovery & Capacity Sizing (Days 1–3)

  
  

  We audit current data pipelines, assess data volumes, map dependencies, calculate optimal Fabric F-SKU capacity, and define the migration architecture.

• Step 2: OneLake Foundation & Medallion Lakehouse Setup (Days 4–7)

  
  

  We provision Fabric workspaces, configure OneLake storage, establish Bronze/Silver/Gold Lakehouse containers, and set up OneLake shortcuts.

• Step 3: Pipeline & PySpark Notebook Migration (Days 8–14)

  
  

  We rebuild and optimize ETL pipelines in Fabric Data Factory, migrate Spark notebooks to Fabric PySpark, and configure automated Delta table compaction.

• Step 4: Direct Lake Semantic Modeling & Power BI Migration (Days 15–18)

  
  

  We build Direct Lake semantic models on Gold Delta tables, tune V-Order indexing, verify sub-second visual performance, and re-point reports.

• Step 5: Governance, Parallel Run & Production Cutover (Days 19–21)

  
  

  We implement Purview lineage, execute parallel validation runs against legacy systems, configure Git CI/CD pipelines, and conduct the team handover.

Book Your Free Scoping Call →

Security, Data Privacy & Confidentiality

Enterprise cloud migration requires the highest level of data integrity and protection:

• In-Tenant Deployment: All data, pipelines, and Fabric workspaces remain 100% inside your organization's Microsoft Azure cloud tenant.

• Zero Third-Party Data Movement: We operate directly within your cloud boundary; your enterprise data never leaves your verified tenant.

• Granular Role-Based Governance: Full integration with Azure Active Directory (Microsoft Entra ID) and OneSecurity access controls.

• Strict Institutional Non-Disclosure: Comprehensive mutual Non-Disclosure Agreements signed prior to reviewing data schemas or architecture.

• 100% Intellectual Property Ownership: All pipelines, notebooks, Lakehouse configurations, and documentation belong entirely to your company.

Investment & Engagement Models

Transparent, milestone-based pricing with guaranteed migration timelines:

Fabric Pilot & Direct Lake Proof of Concept

Typical Scope: Single end-to-end workload, Lakehouse setup, 1 pipeline, Direct Lake Power BI model, capacity benchmarking.

Timeline: 2–3 Weeks

Deliverables: Working Lakehouse, Direct Lake model, benchmark report, architecture roadmap.

Complete Departmental Fabric Migration

Typical Scope: Medallion Lakehouse (Bronze/Silver/Gold), migration of 5–10 pipelines, OneLake shortcuts, full Direct Lake reporting suite.

Timeline: 3–4 Weeks

Deliverables: Production Fabric workspace, migrated pipelines, Direct Lake semantic layer, Purview catalog, team handover.

Enterprise Platform Modernization

Typical Scope: Multi-departmental estate migration (Synapse/ADF/Snowflake), CI/CD DevOps, Purview governance, multi-cloud shortcuts, custom training.

Timeline: 4–6 Weeks

Deliverables: Enterprise Fabric architecture, full pipeline cutover, automated CI/CD pipelines, cost optimization framework, 2 workshops.

What Drives the Cost?

• Number of Pipelines & Complexity: 3 standard SQL pipelines vs. 30 complex nested SSIS packages with custom script components.

• Data Volume & Multi-Cloud Footprint: Terabyte-scale single Azure subscription vs. petabyte-scale multi-cloud estate spanning AWS, GCP, and on-premises databases.

• Semantic Layer Scope: Single targeted departmental report vs. enterprise-wide semantic models with complex DAX and dynamic Row-Level Security.

• DevOps & Governance Depth: Basic workspace setup vs. automated Git integration, Azure DevOps CI/CD deployment pipelines, and full Microsoft Purview compliance.

Get Your Fixed Quote

Flexible Engagement Options

• Fixed-Price Project: Well-defined scope, fixed timeline, and guaranteed deliverables with zero budget overruns.

• Fabric Architecture Retainer: Ongoing monthly guidance from our senior cloud architects to optimize capacity, review notebook performance, and onboard new teams. See our Production Support plans.

Tech Stack & Tooling

• We architect Microsoft Fabric solutions using the official Microsoft modern data ecosystem:

Why Choose Codersarts for Microsoft Fabric Migration

• Early-Adopter Fabric Mastery: We have been architecting Fabric solutions since its inception, understanding the real-world operational nuances of Direct Lake and F-SKUs.

• Deep Lakehouse & Delta Parquet Expertise: We know how to optimize V-Order indexing, schema evolution, and partition layouts for blistering performance.

• Zero-Copy Architecture Focus: We prioritize OneLake shortcuts and Direct Lake modes to eliminate unnecessary data movement and compute expenses.

• Microsoft Certified Data Architects: Work directly with senior cloud data engineers certified in Azure Data Engineering and Fabric Analytics.

• 100% Code & Workspace Ownership: You retain full ownership of all notebooks, pipelines, and workspace configurations with zero proprietary wrapper dependencies.

• Guaranteed Fixed Pricing & Rapid Delivery: Transparent milestone quotes and execution plans delivered within 24 hours of scoping.

Where This Fits in Your AI Project

Microsoft Fabric provides the unified data lakehouse foundation for enterprise generative AI and advanced analytics. Complementary Codersarts services:

• Make Power BI Ready for Copilot & Data Agents: Optimize your Fabric semantic models and configure autonomous Fabric data agents for natural language analytics.

• Build a Power BI Dashboard: Build executive visual reporting applications directly on top of your migrated Fabric Gold Lakehouses.

• Fix a Slow Power BI Report or Broken DAX: Transition struggling legacy import models into lightning-fast Fabric Direct Lake architectures.

• Speed Up Slow Data Processing: Offload heavy data wrangling from slow single-node machines to distributed Fabric PySpark notebooks.

• Clean & Prepare Messy Data: Implement automated Silver-layer data cleansing and deduplication rules inside Fabric Lakehouses.

• Get an AI Architecture Review: Audit enterprise cloud architectures for Fabric migration readiness, security, and capacity optimization.

Designing a lakehouse beyond Fabric? See Build a Data Lakehouse. Fabric Spark notebooks running slow? See Optimize Slow Spark or Databricks Jobs.

Frequently Asked Questions

How much does a Microsoft Fabric migration consulting project cost?

Pricing depends on the number of existing data pipelines, total data volume, source platforms (e.g., Azure Synapse, ADF, SSIS, Databricks), and the number of Power BI semantic models being transitioned to Direct Lake. Following an initial 30-minute architecture review, we provide a transparent, fixed-price quote within 24 hours.

How long does it take to migrate to Microsoft Fabric?

A targeted pilot or departmental proof-of-concept typically takes 2 to 3 weeks. A comprehensive departmental migration with multiple pipelines, a Medallion Lakehouse, and Direct Lake reporting takes 3 to 4 weeks. Large enterprise-scale platform modernizations take 4 to 6 weeks.

What is Direct Lake mode and why is it revolutionary?

Direct Lake mode is a groundbreaking capability in Power BI that allows semantic models to read Delta Parquet tables directly from OneLake storage without importing the data into memory and without translating queries into slow DirectQuery SQL statements. You achieve the lightning-fast performance of in-memory Import mode combined with the real-time freshness and scale of DirectQuery, completely eliminating scheduled dataset refresh times.

What are OneLake Shortcuts and how do they prevent data duplication?

OneLake Shortcuts are virtual pointers that allow Microsoft Fabric to reference data stored in external locations—such as Azure Data Lake Gen2, Amazon S3, or Google Cloud Storage—as if it were residing locally inside your OneLake Lakehouse. You can query external cloud data immediately without copying, syncing, or paying data migration and egress costs.

Can we migrate from Azure Synapse to Microsoft Fabric without downtime?

Yes. We implement a phased parallel migration strategy. We build and validate the new Fabric Lakehouse, pipelines, and Direct Lake models alongside your active Synapse environment. Once automated parallel test runs verify 100% data and performance parity, we execute an immediate, seamless cutover for downstream business users with zero disruption.

What is the difference between a Fabric Lakehouse and a Fabric Warehouse?

A Fabric Lakehouse is designed for Spark-first data engineering and Python data science, storing data in open Delta tables while providing a read-only SQL analytics endpoint. A Fabric Warehouse is designed for traditional data warehousing teams, offering full ACID T-SQL capabilities (INSERT, UPDATE, DELETE) with standard relational transactions. Both store data in open Delta Parquet format in OneLake and can be queried interchangeably.

How do Fabric Capacities (F-SKUs) work and how can we optimize costs?

Fabric uses unified Capacity Units (CUs) billed per second under F-SKUs (from F2 up to F2048). All workloads (Spark, SQL, Data Factory, Power BI) share this pooled capacity. Fabric includes automated capacity smoothing to absorb short-term compute spikes without throttling, and pay-as-you-go capacities can be paused and resumed on schedule to eliminate weekend and overnight costs.

Can our team maintain the Fabric environment after migration?

Yes. We deliver fully documented code, architectural diagrams, and runbooks. Every engagement concludes with a comprehensive handover and a recorded training workshop ensuring your internal data engineers can confidently operate, monitor, and extend the Fabric ecosystem.

What happens if a Direct Lake query encounters an unsupported feature?

If a Power BI Direct Lake query encounters features not yet supported by the Direct Lake engine (such as complex calculated columns or unoptimized data types), it will gracefully "fall back" to DirectQuery mode via the Lakehouse SQL endpoint. We design and validate your Gold tables to ensure 100% of queries remain in pure Direct Lake mode.

Want to learn how to master Microsoft Fabric, Direct Lake, and Lakehouse notebooks yourself?

Read our technical guide: Direct Lake Microsoft Fabric architecture, Fabric lakehouse PySpark notebooks, and OneLake shortcuts on the Codersarts Discuss forum.

Migrate to Microsoft Fabric This Week

Get your data platform migrated to Microsoft Fabric and Direct Lake by Codersarts experts. Eliminate data silos, slash redundant cloud costs, and empower your organization with instant, unified analytics on OneLake today.

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