Power BI Dataflows vs Dataflows Gen2: What Changed and Why It Matters

Power BI Dataflows vs Dataflows Gen2

Dataflows Gen1 transforms data using Power Query (M language) and stores results in Azure Data Lake Storage. Dataflows Gen2 (only in Fabric) transforms data using Power Query AND connects directly to Fabric lakehouse tables — eliminating the separate storage layer. Key difference: Gen2 outputs Delta Lake tables in OneLake that ANY Fabric engine (Spark, SQL, DirectLake) can query. Gen1 outputs are only queryable by Power BI. Migrate to Gen2 when: you've adopted Fabric and want unified storage. Stay on Gen1 when: you're not on Fabric yet. See: Fabric Capacity Planning, DirectLake vs Import.

How It Works in Practice

Enterprise implementations follow structured progression: assessment (2-4 weeks), design (2-4 weeks), build (4-12 weeks), stabilization (2-4 weeks). Total: 10-24 weeks. Organizations that skip assessment spend 40-60% more due to mid-build misalignment.

What Does This Cost?

Consulting rates: $120-350/hr. Typical engagement: $75K-300K over 8-20 weeks. Through Xylity, rates are 20-35% below traditional consulting firms — 4.3-day deployment, 92% first-match acceptance rate. Related: Data Engineering Consulting Cost.

How Do You Get Started?

Start with a 2-week paid assessment ($15K-30K) that tells you exactly what to build, how long it takes, and what it costs. Then deploy pre-qualified specialists through Xylity — 4.3 days to first profile, 92% acceptance rate, 200+ delivery partners across 20+ domains and 22 industry verticals. Related: The True Cost of a Vacant Seat — every week of delay costs $12K-24K.

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