Looker Studio VS Power BI: A Comparative Analysis (2024)

There are two Lookers, and it’s a bit of a mess.

If you’ve ever found yourself talking about Looker and suddenly realized halfway through that no one’s on the same page, you’re not alone. Here’s the thing: there are actually two Lookers.

One is the LookML Looker Core—the analytics powerhouse that’s been around for a while. The other is Looker Studio, formerly Google Data Studio and renamed after Google acquired Looker. Not the best strategic move, if you ask us. This naming confusion has led to plenty of mix-ups, especially among newcomers to the analytics world who innocently refer to Looker Studio as "Looker," unaware that LookML Looker even exists.

And just when you thought it couldn’t get more tangled, Google decided to toss Looker Studio Pro into the mix as the "premium" version of Looker Studio.

That said, in this article, we'll focus mainly on Looker Studio vs Power BI, but you can scroll to the end for a section on how LookML Looker differs from Power BI.

Before you decide on any BI tool, you should be aware of all your options. Here are a few other comparison posts on Looker that we’ve written to help you make a decision:

• Looker vs Tableau
• Affordable & Open-source Looker Alternatives

1. Power BI vs Looker Studio: Data Visualization

When it comes to data visualization, both Looker Studio and Power BI offer robust tools, but they cater to slightly different audiences.

Power BI Visualization & Customization

Extensive Visualization Options

• Supports a wide variety of chart types: bar charts, line graphs, scatter plots, heat maps, and more.
• Allows for highly interactive and dynamic visualizations with features like data drill-downs, filters, and real-time updates.
• Offers custom visuals through its marketplace, enabling integration of additional chart types from the community or third-party developers.

Customization

• Another strong suit of Power BI. Users can modify almost every aspect of a chart, including colors, fonts, data labels, and axes.
• Allows users to create custom themes to ensure visualizations align with company branding.
• AI-powered features suggest the best visualizations based on the data, making it easier for less experienced users to get started.

Looker Studio (formerly Google Data Studio)

Looker Studio (formerly Google Data Studio) takes a slightly different approach. It emphasizes simplicity and ease of use, offering a more limited set of visualization options compared to Power BI.

Simplicity and Ease of Use

• Offers a more limited set of visualization options compared to Power BI, including standard visualizations like bar charts, pie charts, and time series.
• Emphasizes ease of use with a straightforward, drag-and-drop interface, making it accessible for non-technical users.
• Supports standard visualizations like bar charts, pie charts, and time series, but it lacks some of the more advanced visual types found in Power BI.

Google Ecosystem Integration

• Shines in its integration with other Google products, making it easy for to seamlessly integrate with other Google products like Google Analytics, Google Ads, and BigQuery.
• This integration is particularly beneficial for users invested in Google tools, such as marketing teams and small businesses.

Summary

• Power BI: Ideal for users needing a more extensive and customizable range of visualizations, with advanced features for those willing to invest time in learning the tool.
• Looker Studio: Better suited for users looking for a quick, easy-to-use solution, particularly those who are already integrated into the Google ecosystem.

2. Power BI vs Looker Studio: Data Connectivity

Power BI Connectivity

Extensive Connectivity

• Supports a wide range of data sources including SQL Server, Oracle, MySQL, Azure, Salesforce, Google BigQuery, and Excel.
• Offers seamless integration with Excel, making it easy to incorporate spreadsheet data.
• Supports live connections, allowing users to work with real-time data.

DirectQuery Functionality

• Enables querying large datasets directly from the source without importing them into Power BI.
• Ideal for organizations dealing with massive datasets that are impractical to import fully.
• Enhanced data transformation capabilities powered by Power Query for cleaning, reshaping, and merging data before visualization.

Looker Studio Connectivity

Google Ecosystem Integration

• Connects natively to Google products like Google Analytics, Google Ads, Google Sheets, and BigQuery.
• Robust integrations with minimal setup, making it a preferred tool for marketing teams and small businesses reliant on Google tools.

3rd-party Connectors

• Supports connections to non-Google sources like Facebook Ads and MySQL databases.
• Geared towards simplicity and ease of use, though with more limited capabilities compared to Power BI.

User Experience

• User-friendly interface, making it easy for non-data engineers to set up and manage connections.
• While it supports live data connections, it may not be suitable for large, complex datasets or those requiring advanced data transformation features.

Summary

• Power BI: Best for organizations needing to connect to a wide range of data sources, especially large or complex ones. Offers extensive connectivity options and advanced features like DirectQuery, making it ideal for enterprises with diverse data needs.
• Looker Studio: Suited for users within the Google ecosystem or those prioritizing ease of use over advanced connectivity. Provides a streamlined experience with strong Google product integration and user-friendly management.

3. Power BI vs Looker Studio: Advanced Analytics

Advanced analytics is where BI tools start to differentiate themselves by not just showing what the data says, but by helping users understand why things are happening and what might happen next.

Power BI Analytics Capabilities

Advanced Calculations

• Supports DAX (Data Analysis Expressions) for creating custom calculations and complex data models.
• DAX enables advanced operations like time intelligence, ranking, and dynamic segmentation.
• Integrates with R and Python, allowing data scientists to embed advanced scripts and models directly into reports.
• Provides a versatile tool for both business and technical users, offering high analytical flexibility.

AI-Powered Features

• Includes built-in AI capabilities like predictive analytics, anomaly detection, and natural language processing (NLP).
• This feature allows users to uncover insights, predict trends, and identify outliers in their data.

(Example of Power BI Dax)

Looker Studio Analytics Capabilities

Data Modeling Strength

• Data team can utilize LookML (Looker Modeling Language) for defining data relationships and calculations in a reusable way.
• Particularly powerful for organizations needing consistent data models across multiple reports and dashboards.
• Focuses more on data modeling than advanced analytics features.

Limited Predictive Analytics Capability

• Less robust in predictive analytics and AI-driven insights compared to Power BI.
• Can integrate with external tools like BigQuery ML for machine learning models, but these capabilities are not as seamlessly integrated as in Power BI.
• May be less suitable for organizations relying heavily on predictive analytics and machine learning within their BI tool.

(How LookML works)

4. Power BI vs Looker Studio: Dashboarding and Self-Service Analytics

Both Looker Studio and Power BI offer essential features for dashboarding and reporting, but they differ in several key areas. Power BI allows for more advanced customizations, whether Looker Studio brings in better self-service capabilities.

Self-Service and Dashboarding in Power BI

Robust Dashboarding

• Create highly interactive dashboards.
• Supports various visual elements, including charts, graphs, maps, and KPIs.
• Handles large datasets efficiently, enabling multi-source data integration without compromising performance.

Dashboard Customization

• Extensive control over layout, appearance, and behavior of dashboards.
• Flexible options to adjust visual elements and set up dynamic filters.
• Supports real-time data updates for up-to-the-minute insights.

Advanced Reporting

• Tools for creating detailed, formatted reports.
• Schedule automatic report generation and distribution.
• Paginated reports allow for pixel-perfect formatting, suitable for printing or exporting (e.g., PDF, Excel).
• Ideal for organizations with high documentation or compliance requirements.

Dashboarding and Self-Service In Looker Studio

Self-Service Analytics

• User-friendly with an intuitive drag-and-drop interface.
• Allows for easy dashboard creation, even for non-technical users.
• Visually appealing dashboards, though with limited customization compared to Power BI.
• Seamlessly integrates with Google products like Google Analytics and Google Ads.

Reporting and Exploration

• Straightforward reporting features focus on simplicity and ease of use.
• Offers scheduled reports that are automatically generated and distributed.
• Best suited for teams needing quick, accessible reports without extensive customization.

Summary

• Power BI: Ideal for organizations with complex needs, requiring advanced dashboarding, extensive customization, and detailed reporting capabilities.
• Looker Studio: A strong choice for users seeking a self-service, more intuitive tool, especially if already using Google products, with a focus on ease of use rather than deep customization.

5. Power BI vs Looker Studio: Data Governance and Security

When it comes to compliance, both tools adhere to industry standards, but Power BI’s alignment with Microsoft’s compliance framework gives it an edge.

Data Governance and Security Features in Power BI

Integration with Microsoft’s Security Ecosystem

• Leverages Azure Active Directory (AAD) for precise identity management.
• Administrators can implement role-based access controls (RBAC) to restrict data visibility to authorized users.

Data Encryption and Compliance

• Supports encryption of data at rest and in transit, adhering to TLS (Transport Layer Security) standards.
• Provides data loss prevention (DLP) policies and audit logs for monitoring and controlling data usage.
• Particularly beneficial for regulated industries like finance and healthcare.

Row-Level Security (RLS)

• Enables administrators to restrict access to specific data rows based on user roles.
• Ideal for organizations needing to share reports across departments or with external stakeholders while maintaining data segregation.

Data Governance Approach In Looker Studio

Integration with Google Identity Management

• Uses Google Workspace (formerly G Suite) for managing user permissions.
• Simplified access control, especially useful for organizations within the Google ecosystem.

Limitations Compared to Power BI

• Supports basic access controls but lacks advanced features like row-level security or detailed audit logging.
• May be sufficient for smaller organizations or teams with less complex governance needs.

Summary

• Power BI: Best suited for organizations with complex data needs and stringent compliance requirements due to its comprehensive data governance and security features.
• Looker Studio: A good option for teams needing basic governance controls, particularly if they are already using Google’s suite of tools.

6. Power BI vs Looker Studio: Sharing and Collaboration

Collaboration is at the heart of effective data-driven decision-making. Both Looker Studio and Power BI recognize the importance of enabling teams to work together seamlessly, but they approach collaboration in different ways.

Collaboration in Power BI

Real-Time Collaboration

• Multiple users can work on the same report simultaneously.
• See each other's changes in real-time, ideal for quick iterations.

In-Platform Commenting

• Users can leave notes and feedback directly within reports.
• Facilitates discussion and decision-making without leaving the platform.

Publishing and Sharing

• Publish reports to the Power BI service for organizational access.
• Scheduled data refreshes ensure reports are always up-to-date.
• Export reports to formats like PDF and PowerPoint for easy sharing outside the platform.

Collaboration in Looker Studio

Google Suite Integration

• Seamless integration with Google Drive for easy sharing.
• Share reports and dashboards like Google Docs or Sheets.
• Control access with familiar Google sharing settings.

Embedding in Google Products

• Embed reports and dashboards in Google Sites, Gmail, and more.
• Easy dissemination of insights across different platforms.

7. Power BI vs Looker Studio: Embedded Analytics

When it comes to embedded analytics, both Power BI and Looker Studio offer unique strengths.

Let's break down what each one brings to the table and see which might be the right fit for your needs.

Power BI Embedded Analytics

Robust Embedding

• Allows developers to embed fully interactive Power BI reports and dashboards into their applications.
• Deep integration with the Microsoft ecosystem, ideal for organizations using Azure or other Microsoft services.

Customization and Flexibility

• Supports a wide range of customization options. Developers can tailor the appearance and functionality to fit seamlessly within their applications.
• Control over the look and feel of reports, embedding specific visual elements, and integrating with custom authentication systems.
• Extensive control through Power BI’s REST API for a highly customized user experience.

Multi-Tenant Support

• Supports multi-tenant environments, beneficial for SaaS providers.
• Enables delivering personalized analytics experiences to different clients within a single application.

Considerations: Pricing is consumption-based, which could lead to higher costs for applications with high usage volumes.

Looker Studio Embedded Capabilities

Easy Embedding

• Offers embedding capabilities through iframes or embed codes.
• Simple and straightforward method for quickly integrating analytics into websites or internal portals.
• Less flexibility and customization compared to Power BI Embedded.
• Strong integration with Google’s suite of products. Ideal for organizations deeply embedded in the Google ecosystem.
• Best suited for teams familiar with Google’s tools who do not require advanced customization options.

What's about Looker (LookML) vs Power BI?

The table below summarizes the features comparison between Power BI and Looker.

Feature	Power BI	Looker
Deployment on cloud	Yes	Yes
Deployment on-premise	Yes	Yes
Multiple datasource integration	Yes	Yes
SQL support	Yes	Yes
Data modelling	Yes	Yes
Predictive analytics	Yes	Yes
Embedded Analytics	Yes	Yes
Data governance	Yes	Yes
Cache	Yes	Yes
API access	Yes	Yes
Free Version	Yes	No
Free Trial	Yes	Yes

Conclusion

According to the factors discussed in this article, we can agree that both Power BI and Looker are capable business intelligence tools that offer various features including data modeling and predictive analytics. Ultimately choosing the right self-service BI tool boils down to the specific needs and use cases of the organization and the best way to determine if a BI tool fits your requirements is to get your hands dirty and test the platform out in action and then evaluate its performance before making your final decision.

Alternatively, if you’re looking for a self-service BI tool, you might want to check out Holistics, an alternative to Looker. You can start a free 14-day trial with Holistics! No credit card is required.