Data platforms eat up significant percentage of IT budgets, yet most companies use less than half their analytics potential. That’s billions sitting idle while teams wait hours for reports that should take minutes.
A recent Forrester study found organizations implementing Microsoft Fabric saw a 25% increase in data scientist and engineer productivity over three years. The same report reveals a considerable ROI of 379% for the organization that deployed Fabric. This figure shows the real cost savings and business benefits the solution enables.
The problem isn’t lack of data. Companies drown in it. The real issue? Fragmented systems that force teams to spend more time moving data than analyzing it. When your data warehouse, ETL tools, and BI platform don’t talk to each other, every insight costs you time and money.
Microsoft Fabric migration services solve this by unifying your entire analytics stack. But the question isn’t whether to migrate. It’s how to do it without disrupting operations while maximizing your return. Let’s break down exactly how these services turn analytics from a cost center into a profit driver.
Key Takeaways Microsoft Fabric migration delivers 379% ROI and cuts costs by 30% through unified analytics platform consolidation. Automated migration accelerators like FLIP handle 70-80% of the conversion work, reducing migration timelines from months to weeks. Direct Lake mode queries billions of rows instantly without data imports, delivering up to 10x faster report performance.Parallel migration strategies let teams validate Fabric while keeping legacy systems running, eliminating downtime risks. OneLake unified storage eliminates data silos and duplication, reducing storage costs by 40% across all workloads.
Microsoft Fabric Migration Services: Why It is the Need of the Hour? Modern businesses generate more data than ever, but legacy infrastructure holds them back. Here’s what companies face when they stick with outdated data warehouse solutions and fragmented analytics platforms.
1. Data Silos Block Real-Time Decisions When your sales data lives in one system, customer information sits in another, and operational metrics hide in a third, getting a complete picture becomes nearly impossible. Teams waste 30-40% of their time just hunting down information across disconnected platforms.
Organizations using traditional data lakes struggle with fragmentation, where separate systems for storage, processing, and analytics create inefficiencies. By the time you manually combine data from multiple sources, the moment to act has already passed.
2. Infrastructure Costs Keep Climbing Legacy data warehouse platforms charge for storage, compute, backup, disaster recovery, and maintenance separately. You’re paying for database licenses, ETL tool subscriptions, BI platform fees, and data integration software all at once.
Companies maintaining multiple data platforms see operational costs that are 30% higher than unified solutions. Add the staff needed to manage each system, and your total cost of ownership spirals out of control.
3. Scaling Takes Months Instead of Minutes On-premises SQL Server environments require hardware purchases, installation, and configuration when you need more capacity. Cloud platforms like Azure Synapse dedicated SQL pools need manual adjustments to distribution settings, index configurations, and workload management.
Your business doesn’t wait for infrastructure. When marketing launches a campaign or sales closes a major deal, your analytics platform should scale instantly. Legacy systems create problems right when you need speed most.
4. Security Gaps Put Data at Risk Managing security across multiple platforms means different login credentials, separate permission systems, and inconsistent access controls. Each integration point becomes a potential vulnerability where sensitive information could leak.
Compliance gets harder when data governance tools don’t connect with your storage layer, your processing engine, or your reporting platform. You’re manually tracking data lineage and hoping audit logs capture everything regulators need.
5. Teams Can’t Collaborate Effectively Data engineers work in one tool, data scientists use another, and business analysts need yet another platform to build reports. When a Python script runs on someone’s laptop and manually feeds into Power BI , you lose version control, reproducibility, and team knowledge.
Legacy systems store data in isolated locations, making collaboration difficult and forcing teams to work in silos. People recreate the same datasets because they don’t know what already exists. Work gets duplicated while insights get delayed.
Microsoft Fabric cloud migration services deliver more than just a new data warehouse. The platform combines capabilities that previously required five or six separate products into one unified environment.
1. OneLake Unified Data Storage OneLake provides a single data lake that every workload in Fabric can access without copying or moving data. Your data engineering team, data scientists, and Power BI report builders all work from the same source.
Eliminates data duplication and reduces storage costs by up to 40% Built on open Delta Lake format so you’re never locked into proprietary systems 2. Direct Lake Mode for Sub-Second Queries Direct Lake mode lets Power BI query data warehouse tables directly from OneLake storage without importing or caching. Reports load instantly even with billions of rows.
Query performance up to 10x faster than traditional import mode No need to schedule dataset refreshes or manage import windows 3. Built-In AI and Machine Learning Fabric includes AutoML capabilities and integrates with Azure OpenAI without requiring separate services or complex setup. Data scientists build and deploy models in the same workspace where data lives.
Copilot assists with pipeline creation, error resolution, and code generation MLflow integration for model tracking and deployment 4. Real-Time Data Processing Eventhouse and KQL databases handle streaming data from IoT devices, application logs, and event streams. You can analyze data as it arrives instead of waiting for batch processing windows.
Process millions of events per second with automatic scaling Query streaming and historical data together in the same interface Built-in alerting when specific patterns or thresholds occur 5. Serverless Compute Architecture Fabric automatically allocates and deallocates compute resources based on workload demands. You don’t configure distribution strategies, adjust concurrency limits, or manage capacity manually.
Pay only for actual compute used, not reserved capacity sitting idle Scale from zero to thousands of concurrent queries in seconds No performance tuning or index optimization required for most workloads 6. Native Git Integration for Version Control Data pipelines , notebooks, and reports integrate with Azure DevOps or GitHub directly. Your entire analytics codebase gets the same version control, branching, and CI/CD practices as application code.
Track who changed what and when across all development work Roll back to previous versions when something breaks Deploy from dev to test to production with automated pipelines 7. Cross-Workspace Collaboration Multiple teams can work in separate workspaces while still accessing shared datasets through shortcuts. Marketing, finance, and operations maintain their own environments without duplicating company-wide data.
Share data without copying or moving it between workspaces Apply governance policies consistently across all workspaces Teams see only the data they have permission to access 8. Microsoft Purview Integration Data governance capabilities come built into the platform rather than bolted on as an afterthought. Classification, lineage tracking, and access policies apply automatically as data moves through pipelines.
Automatically discover and classify sensitive data like PII or financial information Track data lineage from source systems through transformations to reports Apply row-level security and column-level encryption through centralized policies Cognos vs Power BI: A Complete Comparison and Migration Roadmap A comprehensive guide comparing Cognos and Power BI, highlighting key differences, benefits, and a step-by-step migration roadmap for enterprises looking to modernize their analytics.
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What Do Microsoft Fabric Migration Services Include? Professional migration services handle your complete transition from legacy systems to Microsoft Fabric . This covers moving data from Azure Synapse dedicated SQL pools, on-premises SQL Server databases, or third-party platforms like Oracle and Snowflake into Fabric’s unified environment.
Assessment of current infrastructure including all data sources, workloads, and dependencies Phased migration strategy that minimizes business disruption and maintains operations Testing and validation at each stage to ensure data accuracy and system performance Your database objects need translation from source platform syntax to Fabric-compatible formats. Migration experts use tools like DACPAC files and automated converters to handle tables, views, stored procedures, and functions while addressing platform-specific differences.
Automated T-SQL syntax conversion with AI-powered error detection and fixes Data type mapping to handle differences between source and Fabric warehouse formats Identity column alternatives and index optimization for Fabric’s architecture Existing data integration workflows get rebuilt or adapted to work with Fabric Data Factory. Whether you’re moving from Azure Data Factory , SSIS packages, Informatica, or custom scripts, migration services recreate your data pipelines using Fabric’s capabilities.
Scheduling and orchestration setup to maintain existing data refresh patterns 4. Power BI Report Migration Your existing Power BI reports, dashboards, and datasets transition to Fabric workspaces with enhanced performance features. Migration services update connection strings, implement Direct Lake mode where applicable, and ensure all visualizations work correctly.
Workspace conversion from Power BI Premium to Fabric capacity Dataset optimization to leverage Direct Lake mode for faster query performance Report testing to verify all visuals, calculations, and interactions function properly 5. Data Governance Implementation Migration partners set up Microsoft Purview and configure security policies, access controls, and compliance frameworks from day one. This includes migrating existing roles and permissions to Microsoft Entra ID authentication.
SQL authenticated user conversion to Microsoft Entra ID for secure access Row-level security and column-level permissions configuration across datasets 6. Post-Migration Optimization and Support The work doesn’t stop after go-live. Migration services include performance monitoring, cost optimization, user training, and ongoing technical support to help your team get maximum value from Fabric.
Capacity monitoring and right-sizing recommendations to control costs User training sessions on Fabric features and best practices Continuous improvement support to adopt new capabilities as they release Who Needs Microsoft Fabric Migration Services? 1. Organizations Using Azure Synapse Dedicated SQL Pools Microsoft introduced Fabric as an all-in-one SaaS analytics solution, prompting many companies to evaluate migrating from Azure Synapse dedicated SQL pools Microsoft Learn . If you’re managing distribution settings, indexes, and capacity manually, Fabric offers automated scaling and simplified operations.
Azure Synapse users facing end-of-feature-development concerns Teams spending excessive time on performance tuning and capacity management Companies looking to consolidate Synapse with other Azure services under one platform 2. Companies With On-Premises SQL Server Data Warehouses On-premises infrastructure comes with hardware refresh cycles, maintenance windows, and limited scalability. SQL Server data warehouse migration to Fabric eliminates these constraints while upgrading your analytics capabilities.
Businesses ready to move from capital expenses to operational cloud costs IT teams burdened by physical server maintenance and backup management Organizations needing elastic scaling that hardware upgrades can’t provide SSIS, Informatica PowerCenter, and Talend require special skills and separate licensing. Fabric Data Factory combines these processes into a unified platform with low-code interfaces that reduce development time.
Companies paying high licensing fees for standalone ETL tools Teams struggling to find developers skilled in older ETL technologies Businesses wanting to retire complex on-premises integration servers When you’re juggling separate subscriptions for data storage, ETL, data science notebooks, and BI reporting, costs and complexity increases. Fabric migration services bring everything under one roof with unified billing.
Organizations managing 5+ separate analytics and data tools Finance teams dealing with multiple vendor contracts and renewal cycles Companies unable to track total cost of ownership across fragmented systems 5. Teams Struggling with Data Silos and Integration Challenges Data silos occur when legacy systems store information in isolated locations, making integration difficult. If your analysts spend hours manually combining data from different sources, you need a unified data platform .
Analysts creating duplicate datasets because they can’t find existing work Leadership making decisions with incomplete data due to system disconnects How Kanerika Simplifies Microsoft Fabric Migrations with FLIP Accelerators Enterprises are shifting toward Microsoft Fabric to modernize their analytics, simplify data management , and gain unified governance across pipelines and models. However, manual migration from older Microsoft tools like Azure Data Factory , Synapse, SSIS, or SSAS is slow, complex, and error-prone.
Kanerika’s FLIP migration accelerator changes that. It automates up to 70 to 80 percent of the migration effort, reducing time, cost, and manual work. FLIP ensures a smooth transition to Fabric by preserving business logic, workflows, and dependencies while improving scalability and performance.
We specialize in automated migrations for Azure Data Factory and Synapse, SSIS, and SSAS to Microsoft Fabric.
Modern data teams need unified analytics and AI-driven data integration. pipelines into Fabric Data Factory (FDF) workflows, enabling centralized orchestration, faster execution, and built-in governance.
Pipeline Architecture Assessment & Discovery Our tool scans and maps your current ADF or Synapse environment, analyzing pipelines, dependencies, and orchestration logic to create a full migration blueprint.
Activity Conversion & Fabric Optimization FLIP automatically converts ADF and Synapse activities into native Fabric Data Factory equivalents. It optimizes performance, preserves data flow integrity , and retains your business logic without manual rework.
Integration Mapping & Workspace Configuration The accelerator configures Fabric workspaces, aligns datasets, and validates integration points. It ensures that every migrated pipeline functions exactly as expected in the Fabric ecosystem.
Each migrated pipeline undergoes automated validation and performance tuning. The process ensures data lineage accuracy, correct dependencies, and improved Fabric execution efficiency .
Migrating from SQL Server Integration Services (SSIS) to Microsoft Fabric helps enterprises modernize ETL operations while reducing infrastructure maintenance.
With FLIP, teams upload their existing .dtsx packages, and the accelerator automatically extracts all business logic and transformation rules. It converts them into Power Query–based dataflows optimized for Fabric Data Factory execution.
Key process highlights Extracts SSIS metadata and dependencies automatically Validates structure, logic, and connections before go-live Dataflow Gen2 replicates the logic in Fabric, enabling teams to move from on-prem ETL to cloud-native workflows without losing functionality.
Enterprises moving from SQL Server Analysis Services (SSAS) to Microsoft Fabric can modernize analytics while maintaining business logic and relationships.
FLIP extracts the full SSAS tabular model including hierarchies, roles, and calculation groups. Before migration, it provides a compatibility report outlining expected results and dependencies.
Migration highlights Extracts and converts SSAS metadata into Fabric semantic models Preserves all calculated measures, hierarchies, and roles Maintains identical analytical behavior and query results The result is a ready-to-deploy semantic model that mirrors your SSAS environment, enhanced by Fabric’s scalability and integration with Power BI and OneLake.
Why Enterprises Choose FLIP For Fabric Migration 1. Up To 80 Percent Automation In Conversion And Validation FLIP automates the most complex parts of migration, from code conversion to activity mapping and validation.
2. Faster Migration Timelines With Minimal Manual Work Conventional migrations can take months of manual effort. FLIP reduces that timeline significantly by automating repetitive configuration steps and leveraging prebuilt logic for ADF, Synapse, SSIS, and SSAS migrations. complete their move to Microsoft Fabric within weeks, freeing up teams to focus on optimization instead of setup.
3. Preserved Logic, Dependencies, And Relationships FLIP keeps your data architecture intact. It transfers all transformations, dependencies, and business logic accurately into Fabric, ensuring workflows, hierarchies, and relationships continue to function seamlessly after migration.
Each component that FLIP converts undergoes automated validation to ensure accuracy, correct data lineage, and optimized performance. The tool tests execution times and dependencies before deployment, giving teams complete confidence in stability and reliability from day one.
5. Seamless Integration With The Microsoft Fabric Ecosystem FLIP aligns your migrated assets with Fabric-native capabilities like Dataflow Gen2, OneLake, and Fabric semantic models. Microsoft data tools, allowing your organization to adopt unified governance, analytics, and reporting without manual adjustments.
Frequently Asked Questions Can we migrate to Microsoft Fabric without downtime? Yes, parallel running strategies let you operate old and new systems simultaneously during migration. Teams can validate Fabric performance while keeping legacy systems operational. Phased cutover approaches migrate non-critical workloads first, then transition remaining systems during planned maintenance windows to minimize business disruption
What's the difference between lift-and-shift and redesign migration approaches? Lift-and-shift moves existing architecture to Fabric with minimal changes, offering faster migration at lower cost. Redesign approach completely rethinks your data architecture to maximize Fabric capabilities, providing better long-term performance but requiring more time and resources. Many organizations use a hybrid approach combining both strategies.
How much do Microsoft Fabric migration services cost? Costs depend on data volume, number of pipelines, migration approach, and timeline requirements. Expenses include professional services for assessment and execution, Fabric capacity costs, Microsoft Purview licensing, and training. Many Microsoft partners offer free initial assessments, and the Cloud Accelerate Factory program provides no-cost migration assistance for qualified customers.
Do we need to migrate all our Power BI reports to Fabric? Power BI Pro and Premium Per User licenses continue working unchanged. However, Power BI Premium per capacity retires for agreements renewing after February 2025, requiring migration to Fabric capacity. Migrating reports to Fabric workspaces enables Direct Lake mode for faster performance and access to unified analytics capabilities.
What happens to our existing Azure Synapse resources after migration? Microsoft has announced no current plans to deprecate Azure Synapse. Your Synapse resources can coexist with Fabric or be gradually decommissioned based on your timeline. Migration services help you decide which workloads move to Fabric and which remain in Synapse based on technical requirements and business priorities.
Can Microsoft Fabric handle real-time data streaming? Yes, Fabric includes Eventhouse and KQL databases specifically designed for streaming data. These components process millions of events per second from IoT devices, application logs, and event streams. You can analyze streaming and historical data together in the same interface, eliminating the need for separate real-time processing tools.
How does Microsoft Fabric pricing compare to our current costs? Organizations typically see 30% reduction in operational costs through platform consolidation. Fabric uses unified capacity-based billing instead of separate charges for storage, compute, ETL tools, and BI platforms. Pay-as-you-go pricing means you only pay for resources actually consumed, not idle reserved capacity sitting unused.
What skills does our team need to manage Microsoft Fabric? Teams familiar with Azure Data Factory, SQL Server, or Power BI can transition to Fabric with training. Microsoft Learn offers free certification paths and learning modules. Most migration partners include training as part of their services, helping data engineers, analysts, and administrators become proficient in Fabric capabilities.
s our data secure during the Microsoft Fabric migration process? Yes, migration services use encryption for data in transit and at rest. Fabric maintains SOC 2, ISO 27001, HIPAA, and other compliance certifications. Microsoft Entra ID authentication replaces SQL logins for stronger security. Microsoft Purview provides data classification, access controls, and audit logging throughout the migration process.
