Power BI vs Looker: Which BI Tool is Right for Your Team?

Compare Power BI and Looker for business intelligence and data visualization. Detailed breakdown of pricing, features, and which tool fits your analytics needs.

Updated 2026-10 · 2026

Power BI

Microsoft's business intelligence platform with deep Office 365 integration

$10-20user/month

Strengths

+Excellent integration with Microsoft ecosystem (Excel, Azure, Office 365)
+Strong data modeling capabilities with DAX language
+Affordable pricing for small to medium teams

Weaknesses

-Steep learning curve for advanced features and DAX
-Limited collaboration features on free tier
-Performance issues with very large datasets

Best for

Teams already using Microsoft products who need affordable BI with strong Excel integration

Looker

Google Cloud's enterprise BI platform with LookML modeling layer

Customcontact sales

Strengths

+Powerful LookML modeling language for version-controlled data definitions
+Excellent for embedded analytics in applications
+Strong governance and centralized data modeling

Weaknesses

-Expensive enterprise pricing, no free tier
-Requires technical expertise to set up and maintain LookML
-Steeper learning curve than drag-and-drop tools

Best for

Large enterprises with technical teams who need centralized data governance and embedded analytics

Feature Comparison

Feature	Power BI	Looker
Free Tier	Yes (Power BI Desktop for local use)	No
Starting Price	$10/user/month (Pro)	Custom enterprise pricing
Data Modeling	DAX language, Power Query	LookML (SQL-based)
Visualization Options	Extensive library, custom visuals marketplace	Good selection, customizable
Collaboration	Workspaces, sharing (Pro+ required)	Built-in, enterprise-grade
Data Sources	100+ connectors, strong Microsoft integration	60+ connectors, strong GCP integration
Mobile Apps	iOS, Android (full-featured)	iOS, Android
Embedded Analytics	Available (Premium required)	Excellent, core strength
Version Control	Limited (deployment pipelines in Premium)	Git-native for LookML models
Learning Curve	Moderate (steep for DAX)	Steep (requires SQL/LookML knowledge)
Real-time Data	Yes (DirectQuery, streaming)	Yes (persistent derived tables)
Self-Service BI	Strong for business users	Requires technical setup first

The Verdict

Power BI wins for budget-conscious teams already in the Microsoft ecosystem, offering powerful features at $10-20/user/month with a free desktop option. Looker is the better choice for large enterprises needing centralized data governance, embedded analytics, and Git-based workflows, but expect to pay significantly more. For most small to medium teams, Power BI's pricing and Microsoft integration make it the practical choice.

How to switch from Power BI to Looker

1Identify and document every underlying data source (SQL database, data warehouse, Excel file, API) feeding your current Power BI reports — Looker needs to connect directly to these sources, not to Power BI itself.
2Use Power BI's 'Export data' feature on key visuals to pull a CSV/Excel snapshot of current report outputs, so you have a reference baseline to validate against once the same reports are rebuilt in Looker.
3Connect your data warehouse or database (e.g., BigQuery, Snowflake, Postgres) to Looker and set up the initial LookML project to define dimensions and measures that replicate your DAX calculations.
4Rebuild each Power BI report as a Looker Explore and dashboard, translating DAX measures and Power Query transformation logic into LookML and SQL.
5Recreate scheduled refreshes, email/Slack alerts, and any embedded analytics or Teams-based sharing workflows using Looker's native scheduling and embedding tools.
6Run both tools in parallel for 2-4 weeks, compare output numbers against your exported Power BI baseline, then migrate user permissions and fully cut over once the Looker dashboards are verified.

Power BI vs Looker: common questions

How do I export my data from Power BI before switching to Looker?+

Power BI doesn't export reports into Looker's format — instead you need to identify the underlying data sources (databases, warehouses, Excel files) each report connects to and point Looker at those same sources directly. For report-level data you can use Power BI's 'Export data' option on visuals to pull results out as CSV or Excel, but this is only useful for one-off reference, not for rebuilding the live model.

What features do I lose moving from Power BI to Looker?+

You lose DAX-based calculations, Power Query transformations, the custom visuals marketplace, and tight native integration with Excel and Office 365. You gain Git-based version control and LookML's centralized governance instead, but anything built around Excel workflows will need to be rebuilt.

Is Looker's free tier enough for a small team, or should we stick with Power BI?+

Looker has no free tier at all — it's custom enterprise pricing with sales contracts, typically a poor fit for small teams. Power BI's free Desktop app plus $10/user/month Pro tier is almost always the more practical and affordable choice unless you specifically need LookML governance or embedded analytics at scale.

Does Looker integrate with Microsoft tools like Excel and Teams?+

Looker has no native Excel integration and limited support for Microsoft-centric workflows; it's built around Google Cloud Platform and BigQuery. If your team relies heavily on Excel exports or Teams-based sharing, expect to replace those habits with Looker's web-based dashboards and Slack/email scheduling instead.

How much will Looker cost over time compared to Power BI?+

Power BI scales predictably at $10-20 per user per month, so costs grow linearly with headcount. Looker uses custom enterprise contracts that are typically negotiated annually and can run into tens of thousands of dollars per year even for mid-sized teams, so total cost of ownership is usually significantly higher than Power BI over a 2-3 year period.