Microsoft has announced that Power BI Premium capabilities are now part of Microsoft Fabric. With plans to retire certain Power BI licensing options by January 2025, organizations are encouraged to transition to Fabric. Here’s what you need to know about the migration process and what you should do.
Current State Architecture
If we consider a very simple Power BI architecture,
Moreover, In a traditional Power BI Premium setup, data flows through the following stages:
In this current setup, data is staged and hosted in workspace-specific data flows, which directly feed into Power BI datasets.
Challenges with Existing Power BI Data Flows
While Power BI is the most widely used business intelligence platform globally, its existing data flows do have some limitations you should be aware of:
Limited Scalability
Data flows are often confined to individual workspaces, causing governance and performance issues at scale.
Complexity with Linked Data Flows
Linked data flows can become messy, especially when performing complex transformations.
Performance Bottlenecks
Large datasets in Power BI Premium can slow down refreshes and affect overall report performance.
Why Adopt Fabric?
Microsoft Fabric is an all-in-one SaaS platform that brings together Microsoft’s core tools and services for data management, integration, and analysis.
Also, Power BI Premium is deprecated and absorbed in into Fabric. So, you have Fabric capacity instead of your Premium capacity now. So, all the additional features are now in your fingertips.
For those not used to Premium, here why adopting Fabric might be the right move for you:
Lower Entry Point & Cost-Effectiveness
Fabric provides more options and computational power—at a lower cost to legacy Power BI Premium subscriptions. Compared to $5k a month, it starts at under $300/month.
Scalability & Flexibility
Fabric’s Lakehouses, Dataflow Gen2, and Pipelines offer greater flexibility and scale for both current and future needs.
Future-Proof Architecture
By unifying data and analytics, Fabric simplifies data pipelines, integrations, and advanced capabilities (e.g., AI and data science), making it a forward-looking choice.
Proposed Fabric Architecture
Migrating from Power BI Premium / (Pro or PPU) to Fabric might seem like a complex process, but we’re here to break it down for you. Our guiding principle is “Create Value Today, Build for Tomorrow”. We propose a two-stage migrating process that will help you smoothly transition with minimal disruptions, without fear of losing access to your existing work.
Here is how our two-stage process will benefit you:
Stage 1: Achieve Immediate Value
If you’re looking to get started immediately and begin realizing value with a quick setup, this stage is the answer. In this first stage, the goal is to create a smooth transition to Microsoft Fabric with minimal impact on your current workflows. This stage focuses on getting your data into Fabric and taking advantage of its performance improvements.
Step 1: Create an EDW (Curated) Lakehouse
Step 2: Load Existing Data Flows into EDW Lakehouse
Step 3: Create Views on EDW Lakehouse
Step 4: Connect Power BI Reports to EDW Lakehouse
If this process is carried out successfully, you should be left with a quick modernization of your data pipeline, delivering immediate performance benefits with minimal disruption to end users.
Stage 2a: Remove Debt (Simple Medallion)
Once you got immediate value, we can start removing the redundant portion. Based on your requirements, you might not need the separation of Extract and Transformation layer meaning the original set up in good enough.
So, all we are going to do is replace the old Dataflow Gen 1 Staging.
Step 1: Copy the PowerQuery from Gen1 to Gen2 Dataflow
Step 2: Select the Raw Lakehouse for the destination
Step 3: Reconfigure Views in EDW Lakehouse
Step 4: Update Pipelines for Orchestration
Step 5: Delete staging Gen1 Dataflows
Overall, results in a medallion-like architecture, providing clarity, traceability, and scalability for your data pipeline, ensuring that your infrastructure is future-proof and able to scale with your business needs.
The best part users will never get impacted.
Stage 2b: Full Medallion ELT Method
Medallion architecture offers a powerful advantage by clearly separating data extraction from transformation—a key benefit for audit trails and data lineage. This approach not only streamlines the processes of data ingestion, transformation, and reporting but also ensures that your system can scale and evolve alongside your organization’s growth. Its scalable, modular, and future-proof design forms the backbone of a resilient data ecosystem, fully equipped to handle increasingly complex analytics and business intelligence demands.
Step 1: Change Dataflow Gen2 to only bring the untransformed Raw Data from source
Step 2: Create a Transform Lakehouse
Step 3: Create Gen2 Dataflow, Pipeline, or View to create the transformations and set destinations Transform Lakehouse
Step 4: Update the view in the EDW
Step 5: Orchestration & Reporting
This concise medallion architecture ensures clarity, traceability, scalability, and futureproofing, adapting effortlessly to evolving business needs.
Benefits of Transitioning to Microsoft Fabric
Performance Gains: The use of modern storage formats (Parquet/Delta) yield faster refresh times and quicker query responses.
Simplified Architecture: Separating the Raw and EDW layers creates a clear distinction between data ingestion and serving. This separation clarifies ownership, allows better governance, and improves performance tuning.
Scalable Solution: Microsoft Fabric is built to scale. Unlike Power BI Premium, Fabric is designed to support data science, AI, and advanced analytics, making it the ideal solution for organizations looking to expand their analytics capabilities.
What are Your Next Steps?
To set your organization up for success when it comes to your transition to Microsoft Fabric, here are our recommended steps to follow up:
- Trial the Stage 1 Migration
Select a few key data flows to move into the EDW Lakehouse and test the performance improvements.
- Implement Medallion Architecture Setup
Set up the medallion approach (Raw + Transform + EDW) using methods like dataflow gen 2, visual query, SQL views, etc.
- Scale with Pipelines
Automate and monitor your data flows using Pipelines to ensure reliability and compliance.
By taking these steps, you can minimize disruption for business stakeholders while deliberately building a robust, future-proof analytics environment in Microsoft Fabric.
The beauty of Fabric is that as you grow and gain new skill (Python, SQL, KQL), you can continue to create value for your organization and integrate that into your Data & AI journey.
