Power BI Pricing (2026): What It Actually Costs

Power BI Pro at $10/user/month is the most affordable enterprise BI license on the market. But Premium features, capacity pricing, and Azure consumption costs can push the real number higher.

Power BI pricing starts at $10/user/mo (Monthly or Annual) for the Power BI Pro plan.

Published Pricing

Premium Per User (PPU)

$20/user/mo
Monthly or Annual
  • 100 GB max dataset size
  • 48 daily data refreshes
  • Paginated reports
  • AI features and dataflows
  • Deployment pipelines

Premium Per Capacity (P1)

$4,995/mo
Annual
  • Dedicated cloud compute resources
  • Unlimited free viewers
  • Larger dataset sizes
  • XMLA endpoint access
  • Autoscale option

Power BI Embedded

Usage-based
Azure consumption
  • Embed in custom applications
  • Azure capacity pricing
  • No named user licenses needed
  • White-label capabilities

The Bottom Line

Read the full Power BI review โ†’

Frequently Asked Questions

Is Power BI free with Microsoft 365?

Power BI Pro is included with Microsoft 365 E5 subscriptions at no additional cost. Other M365 plans do not include Power BI. Power BI Desktop (the authoring application) is a free download for anyone.

When should I upgrade to Premium?

Consider Premium Per User ($20/user/month) when you need datasets larger than 1 GB, paginated reports, or AI features. Consider Premium Per Capacity ($4,995/month) when you have 250+ report viewers, since it eliminates per-user viewer costs.

How does Power BI pricing compare to Tableau?

Power BI Pro ($10/user/month) is 7.5x cheaper than Tableau Creator ($75/user/month). Even Premium Per User ($20/month) is less than half of Tableau Explorer ($42/month). The cost advantage narrows at enterprise scale with Premium Capacity, but Power BI remains significantly cheaper in most deployments.

About the Author

Rome Thorndike has spent over a decade working with B2B data and sales technology. He led sales at Datajoy, an analytics infrastructure company acquired by Databricks, sold Dynamics and Azure AI/ML at Microsoft, and covered the full Salesforce stack including Analytics, MuleSoft, and Machine Learning. He founded DataStackGuide to help RevOps teams cut through vendor noise using real adoption data.