Microsoft Fabric vs Looker Navigating the Business Intelligence Landscape

Microsoft Fabric vs Looker stand out as prominent contenders, each offering robust features for data exploration, visualization, and analysis. This blog post aims to provide a comprehensive comparison of Microsoft Fabric and Looker, empowering you to make an informed decision for your organization’s BI needs.

Introducing the Contenders

Microsoft Fabric

Launched in 2022, Microsoft Fabric emerges as a versatile BI platform designed to cater to diverse data requirements. It integrates seamlessly with the Microsoft ecosystem, offering a unified data platform encompassing data warehousing (Azure Synapse Analytics), data governance (Purview), advanced analytics (Azure Databricks), and business intelligence (Power BI).


Acquired by Google in 2020, Looker is renowned for its user-friendly interface and robust data exploration capabilities. It excels at transforming raw data into actionable insights through intuitive dashboards and visualizations. Looker is suitable for businesses of all sizes, with a focus on data exploration and discovery.

Target Audience and Use Cases

Microsoft Fabric

Fabric is ideal for organizations deeply entrenched in the Microsoft ecosystem. Its seamless integration with existing Microsoft tools like Excel and Power BI simplifies the data workflow for users. Fabric caters well to complex data needs with its data lakehouse architecture, making it suitable for enterprises dealing with vast and diverse data sets.


Looker appeals to businesses of all sizes, offering an intuitive interface and robust data exploration capabilities. It is popular among business analysts and data-driven teams for uncovering trends and patterns within data. Looker facilitates data-backed decision making through its user-friendly approach to data exploration.

Key Feature Comparison

Data Ingestion and Management

Microsoft Fabric: Leverages Azure Synapse Analytics for data warehousing, offering a data lakehouse architecture for storing structured, semi-structured, and unstructured data.

Looker: Relies on external data sources for ingestion and integrates seamlessly with popular cloud data warehouses like Google BigQuery and Amazon Redshift.

Data Security and Governance

Microsoft Fabric: Tight integration with Microsoft Purview ensures data security and compliance, offering features like data lineage tracking and role-based access control.

Looker: Provides role-based access control and data security features, though may require additional tools for comprehensive data governance.

Data Exploration and Visualization

Microsoft Fabric: Relies primarily on Power BI for data visualization, offering a wide range of pre-built connectors and functionalities for creating interactive dashboards and reports.

Looker: Boasts a robust built-in visualization engine and strong search functionality for exploring data, allowing users to create a variety of charts and graphs.

Development and Customization

Microsoft Fabric: Leverages Azure Databricks for advanced analytics and data transformation, enabling developers to utilize languages like Python and SQL for complex tasks.

Looker: Utilizes LookML, a proprietary data modeling language, for defining data, enabling developers to customize data models and calculations.

Learning Curve and User Experience

Microsoft Fabric: The learning curve for Fabric may be steeper, particularly for users unfamiliar with the Microsoft ecosystem, but offers streamlined workflows once users are acclimated.

Looker: Features a user-friendly interface with drag-and-drop functionality, making it accessible to business analysts and non-technical users.


Microsoft Fabric: Utilizes a consumption-based pricing model for Azure Synapse Analytics and other services within Fabric, offering flexibility in scaling based on usage.

Looker: Employs a tiered pricing structure based on the number of users accessing the platform, potentially becoming costly for larger deployments.

Comparison table highlighting key features of Microsoft Fabric vs Looker:

Feature Microsoft Fabric Looker
Data Ingestion Azure Synapse Analytics External data sources (e.g., BigQuery)
Data Visualization Power BI Built-in visualization engine
Data Security Microsoft Purview Role-based access control
Customization Azure Databricks LookML (proprietary data modeling language)
User Experience Learning curve for Microsoft ecosystem users User-friendly interface
Pricing Consumption-based Tiered pricing based on users

Choosing the Right Platform

The optimal BI platform depends on your organization’s specific needs and priorities. Consider factors such as existing IT infrastructure, data complexity, team skillsets, and budgetary constraints when evaluating Microsoft Fabric and Looker.

The Future of BI

Both Microsoft Fabric and Looker are continuously evolving to meet the evolving demands of BI. Key trends shaping the future of BI include:

  • Artificial Intelligence and Machine Learning: Integration of AI and ML capabilities for automated insights generation and predictive analytics.
  • Natural Language Processing: Advancements in NLP for intuitive data exploration using natural language queries.
  • Embedded Analytics: Embedding BI functionalities within business applications for contextual data insights.
  • Democratization of Data: Making BI tools more user-friendly and accessible to a broader range of users within organizations.


Microsoft Fabric and Looker offer distinct advantages in the BI landscape, catering to different organizational needs. By assessing your requirements and considering the strengths of each platform, you can make an informed decision to unlock the full potential of your data-driven initiatives.

Choosing the right BI platform is an investment in your organization’s data-driven decision-making capabilities. Carefully weigh the features, integrations, and pricing structures of Microsoft Fabric and Looker to ensure alignment with your business objectives.

External Links

  1. Microsoft Fabric
  2. Looker

Frequently Asked Questions (FAQs)

  1. What is the pricing model for Microsoft Fabric and Looker?
    • Microsoft Fabric follows a consumption-based pricing model, while Looker employs a tiered pricing structure based on the number of users.
  2. Which platform is more suitable for organizations heavily invested in the Microsoft ecosystem?
    • Microsoft Fabric offers seamless integration with existing Microsoft tools, making it ideal for organizations entrenched in the Microsoft ecosystem.
  3. Does Looker have its own data warehouse?
    • No, Looker relies on external data sources for data ingestion but integrates seamlessly with popular cloud data warehouses like Google BigQuery and Amazon Redshift.
  4. What programming languages are supported for customization in Microsoft Fabric and Looker?
    • Microsoft Fabric leverages languages like Python and SQL for customization, while Looker utilizes LookML, a proprietary data modeling language.
  5. Which platform is more user-friendly for non-technical users?
    • Looker features a user-friendly interface with drag-and-drop functionality, catering to business analysts and non-technical users.

By addressing these FAQs, organizations can gain further clarity in their decision-making process when choosing between Microsoft Fabric and Looker for their BI needs.