Synapse and BYOD were built for yesterday’s analytics demands. As data volumes, refresh cycles, and reporting dependencies scale, these environments become harder to govern, costlier to run, and slower to adapt. Microsoft Fabric eliminates that fragmentation by centralizing storage, compute, pipelines, modeling, and BI into one unified platform.
For organizations that depend on consistent, high-performance analytics, the shift to Fabric is now a structural necessity. DynaTech guides this transition with a migration approach that maps your current pipelines, warehouses, security model, and reporting layers into a streamlined Fabric architecture built for speed, control, and predictable cost.
Before any migration begins, the organization must map its current data estate with precision. Synapse and BYOD deployments can be highly customized, so a thorough technical assessment prevents surprises downstream.
Key assessment checkpoints include:
This inventory helps map which assets move directly, which require re-engineering, and which need to be retired.
Fabric supports a wide spectrum of workloads, so each category must be clearly identified:
This classification determines which Fabric components (Lakehouse, Warehouse, Data Engineering, Data Factory, Real-Time Analytics) should be used.
For each current asset, define its destination within Fabric:
This architectural blueprint prevents inconsistent environments and sets expectations for data teams.
This unified OneLake-centric design aligns closely with modern lakehouse patterns such as the Medallion Architecture in Microsoft Fabric, which helps enterprises standardize ingestion, transformation, and analytics layers.
A major decision:
Do you run the old and new systems in parallel, or switch at once?
Most organizations adopt a phased cutover:
This minimizes risk and business disruptions.
Once the plan is established, the next step is provisioning and preparing Fabric for incoming workloads.
Fabric pricing is based on capacity units (CUs) under SKUs like F2, F4, F8, F16, F32, and beyond.
Selection depends on:
Most mid-sized organizations begin with F4–F8, while larger data teams or heavy engineering workloads may need F16 or higher.
Fabric centralizes all storage inside OneLake, so the primary setup involves:
Replacing multiple storage layers with OneLake drastically reduces fragmentation.
Fabric offers multiple paths:
During migration, teams often streamline redundant pipelines, improving performance and governance.
Fabric Warehouses support T-SQL, scalable compute, and seamless Data i with Power BI.
Data models and semantic layers are recreated to ensure:
Before data flows are redirected:
This step prevents go-live bottlenecks.
Historical and incremental data migration must be handled systematically.
Data is typically migrated through:
Teams must ensure schema alignment, partition consistency, and metadata correctness.
Once historical data lands:
Validation checks include:
Only after this verification is the system ready for cutover.
The transition to Fabric requires careful coordination.
Power BI datasets, dashboards, paginated reports, and metrics shift to Fabric semantic models.
Teams must learn:
Once Fabric is stable:
This is where organizations begin seeing the financial advantage.
Many organizations adopt Fabric at this stage because it is already outpacing Synapse in the modern data landscape, especially for unified governance, real-time analytics, and BI consolidation.
Reserved capacity discounts help long-term cost management if workloads are stable.
Some organizations cannot migrate fully in one step.
This gives teams flexibility while maintaining data integrity.
Microsoft Fabric uses a capacity-based pricing model built on Fabric Capacity Units (CUs). Instead of paying separately for compute engines (Spark, SQL, Data Factory, Real-Time Analytics, Fabric Power Bi), Fabric consolidates everything under one capacity. Storage is billed separately through OneLake.
Below is a clear breakdown of how pricing works in 2025, what components you actually pay for, and what organizations should account for during budgeting.
Fabric offers multiple SKUs—F2, F4, F8, F16, F32, F64, and higher—each representing increasing compute throughput for pipelines, SQL workloads, notebooks, machine learning, BI refreshes, and real-time processing.
Approximate Pay-As-You-Go (PAYG) monthly pricing looks like this:
For predictable workloads (24x7 ETL, BI, SQL analytics), reserved commitment is significantly cheaper.
Approximate examples:
Reserved capacity suits medium and large teams planning long-term adoption.
Storage is billed separately across regions, typically:
OneLake’s advantage is a single storage layer, meaning:
No duplicate copies for engineering, warehousing, real-time analytics, or Power BI. One data copy → multiple workloads.
Heavy users (IoT, telemetry, large historical data) must consider long-term storage growth.
User licensing differs based on the Fabric SKU you run:
Smaller setups require both Fabric capacity + user-based licensing.
Large enterprises (F64+) consolidate BI licensing under Fabric.
A mid-size analytics team using Fabric for:
might typically run on F8 or F16.
Estimated monthly cost:
This is significantly simpler—and often cheaper—than maintaining separate Synapse, ADLS, Data Factory, and Power BI Premium setups.
Microsoft Fabric supports autoscale for Spark-based workloads, allowing compute to scale automatically during peak processing windows. When enabled, Spark jobs can temporarily consume additional capacity beyond the base SKU to complete heavy transformations or large batch loads faster.
Key considerations:
Autoscale helps balance performance and cost by avoiding permanent overprovisioning while still meeting processing deadlines.
If most users only consume reports:
But large historical data migrations may temporarily increase storage and pipeline cost during transition.
A Fabric migration is not just a lift-and-shift. It requires:
DynaTech brings deep expertise in Dynamics 365, Synapse, BYOD, and Microsoft Fabric, along with migration accelerators that shorten timelines and reduce rework. Our teams help organizations restructure their analytics landscape, improve data reliability, and optimize cost using Fabric’s unified platform capabilities.
Moving from Synapse or BYOD to Microsoft Fabric is a chance to simplify your data environment, consolidate tools, reduce long-term cost, and build a single, well-governed analytics platform. With the right migration plan, Fabric becomes a stable foundation for analytics, engineering, and reporting at scale.
If your organization is planning this transition, DynaTech, as a Microsoft Solutions Partner, can help you execute it with accuracy and speed.
Visit our website to learn how we support end-to-end Fabric migrations.
Planning a structured migration from Synapse or BYOD to Microsoft Fabric? Explore DynaTech’s Microsoft Fabric migration services for enterprise-ready analytics.