Table of Contents

Looker vs Tableau: Comparing Data Visualization Giants


Table of Contents


Within the landscape of business intelligence (BI) solutions, Looker and Tableau emerge as frontrunners, offering robust capabilities for data visualization and dashboard development. Whether your goal revolves around elucidating datasets or crafting elaborate dashboards, both platforms provide comprehensive tools to meet diverse analytical requirements.


However, discerning the unique attributes that distinguish Looker from Tableau is crucial in determining which solution aligns best with your business objectives. By delving into the intricacies of each platform, you can pinpoint the one that resonates most effectively with your organizational needs and analytical workflows.


This article serves as a comprehensive guide to understanding Looker and Tableau, delving into their respective features, pricing models, and application scenarios. By exploring these facets in depth, readers gain valuable insights into the distinctive strengths and capabilities of each platform, enabling them to make well-informed decisions regarding their BI tool selection.


Moreover, in addition to elucidating the disparities between Looker and Tableau, this article also offers recommendations for cost-effective courses designed to enhance proficiency in data visualization. By investing in skill development through these suggested resources, individuals can fortify their expertise and leverage the full potential of their chosen BI platform, thereby augmenting their professional acumen and driving impactful data-driven decision-making within their organizations.

The table below outlines a comprehensive comparison between Looker and Tableau, presenting key aspects such as pricing, integration, features, and best use cases:



Aspect Looker Tableau
Price Looker’s pricing varies but typically starts at around $35,000 per year Tableau’s pricing structure varies depending on the number of users
Integration Looker is seamlessly integrated into the Google Cloud Platform (GCP) and can easily integrate into various BI workflows Tableau offers native integration with Salesforce CRM, Slack, and other BI workflows
Features Looker provides robust features including data visualization, analysis, modeling, version control, simultaneous collaboration, LookML, and a marketplace for Looker Blocks Tableau offers data visualization, analysis, modeling, and a user-friendly drag-and-drop interface for ease of use
Best Use Case Looker is well-suited for larger organizations with established data teams capable of managing dashboards with LookML Tableau is ideal for smaller organizations with limited data team members needing accessible data visualizations



This detailed comparison aids in making an informed decision regarding the selection of the most suitable data visualization tool based on specific organizational requirements, budget considerations, and desired features.

What is Looker?

Looker stands as a pivotal data visualization tool nestled within the expansive ecosystem of Google’s Cloud Platform (GCP), a robust suite comprising interconnected solutions like BigQuery, Cloud Storage, and CloudSQL. Designed to empower organizations, Looker facilitates the creation of dynamic dashboards and insightful reports, leveraging data visualization techniques to render complex datasets into easily comprehensible graphs and charts. This transformation enables stakeholders to glean actionable insights and steer their decision-making processes with confidence, grounded in data-driven intelligence.


At the core of Looker’s functionality lies its proprietary language, Looker Modeling Language (LookML), ingeniously crafted around the familiar Structured Query Language (SQL). This framework simplifies data modeling tasks, rendering it accessible to data professionals with prior SQL experience. Moreover, LookML empowers technical users such as data engineers to fashion bespoke data models resembling user-friendly applications, catering to the diverse needs of non-technical users who interact with data regularly within their roles.


Regarding pricing, Looker operates on a scalable model, with subscription costs varying based on factors like connected data sources, user count, and deployment scale. While offering unparalleled versatility, Looker’s technology comes with a price tag, typically starting at around $35,000 per year and scaling upward in accordance with organizational requirements.


Key features distinguish Looker as a formidable business intelligence tool:


1. Integrated Platform: Seamlessly integrates into existing BI solutions, facilitating seamless adoption within established workflows.


2. LookML: Empowers data professionals to develop custom applications and tools tailored to user requirements.


3. Looker Blocks: Enables the utilization of pre-built code snippets, known as “blocks,” ranging from comprehensive data models to specialized visualizations sourced from the Looker Marketplace.


4. Embedded Analytics: Provides real-time data analysis tools, furnishing users with actionable insights at their fingertips.


5. Version Control: Offers robust version control capabilities, ensuring transparency and accountability in the modification process.


Looker finds application across various business scenarios, primarily in data visualization endeavors. For instance, organizations utilize Looker to transform sales data into informative visualizations delineating quarterly sales trends, product performance breakdowns, and regional sales dynamics. Moreover, Looker’s scalability ensures its alignment with organizational growth trajectories, obviating the need for costly overhauls in BI architecture as businesses expand their footprint.


In essence, Looker epitomizes a sophisticated yet accessible tool, empowering businesses of all sizes to harness the power of data visualization and drive informed decision-making in an ever-evolving landscape of analytics and insights.

What is Tableau?

Tableau emerges as a versatile data visualization tool, serving as the cornerstone for crafting dynamic dashboards and insightful reports drawn from an organization’s diverse data sources. At its core, Tableau encompasses a desktop application, Tableau Desktop, facilitating the creation of visualizations that can be shared either via a dedicated server, Tableau Server, or through the cloud-based Tableau Cloud platform.


Renowned for its user-friendly interface, Tableau simplifies the visualization process by enabling users to effortlessly create visualizations through intuitive drag-and-drop interactions with pre-existing data fields. The platform’s innate ability to interpret datasets and categorize them into distinct dimensions and measurements, both existing and generated by the application itself, renders Tableau accessible even to non-technical users, empowering them to derive insights from data and seamlessly share them with peers.


Pricing for Tableau varies depending on the type and number of users, categorized into three tiers: Tableau Creators, Tableau Explorers, and Tableau Viewers. Each user type incurs a monthly fee, granting access to different functionalities ranging from full spectrum capabilities for Creators to viewing pre-existing visualizations for Viewers.


Key features that distinguish Tableau as a leading BI tool include:


1. Integrated Platform: Tableau offers flexibility by operating on-premises, in the cloud, or seamlessly integrating within the Salesforce CRM. It also boasts integration capabilities within online platforms like Slack.


2. Data Analytics: Users can leverage Tableau for building visualizations, employing AI-driven statistical modeling, and utilizing natural language processing to interact with the platform. Real-time analytics further enrich the user experience by providing updated information on-demand.


3. Ease of Use: Tableau’s intuitive interface makes it a preferred choice for users seeking an easy-to-use platform, enabling them to create visualizations with minimal prior experience in data manipulation.


4. Sharing and Collaboration: Tableau facilitates seamless sharing of insights among colleagues through publication on shared servers or cloud-based platforms. Mobile applications enhance accessibility, allowing users to access visualizations on-the-go.


Tableau finds application across various use cases, akin to Looker, enabling businesses to leverage visualizations, dashboards, and reports for informed, data-driven decision-making. For instance, an SEO marketing team might utilize Tableau to graphically represent monthly site visitor metrics, demonstrating traffic growth resulting from recent marketing campaigns.


Tableau’s exceptional ease of use positions it as an invaluable asset for businesses aspiring to cultivate a data-driven culture without relying on an extensive data team. Moreover, its scalability ensures seamless adaptation to evolving business needs, empowering organizations to leverage data insights effectively as they grow.


Here’s an overview of the feature comparison between Looker and, along with insights on selecting the right business intelligence (BI) software for your organization:


Feature Comparison Overview


1. Data Visualization:

– Looker: Offers dynamic dashboard filters and mapping features for enhanced chart creation.

– Tableau: Specializes in visualization dashboards, providing pre-made templates and a user-friendly wizard feature.

– Advantage: Tableau excels in offering a variety of visualization options and ease of use for non-technical users.


2. Integration:

– Looker: Integrates with big data platforms and databases, executing queries without data extraction.

– Tableau: Offers over 200 connectors for various data sources, including RDBMS, spreadsheets, and cloud platforms.

– Advantage: Tableau’s extensive connector library provides versatile data integration capabilities.


3. Data Modeling:

– Looker: Utilizes LookML for reusable and flexible data modeling, supported by pre-built modeling tools called Looker Blocks.

– Tableau: Employs snowflakes and dimensional data models to enhance query performance.

– Advantage: Looker’s LookML offers deeper analytical insights and flexibility in data modeling.


4. Reporting:

– Looker: Provides basic reporting templates.

– Tableau: Enables users to create customized reports with extensive connectors for dashboard and report creation.

– Advantage: Tableau’s customizable reporting features offer greater flexibility for users.


5. Speed:

– Looker: Users may experience slower report sharing, requiring several hours.

– Tableau: Enables quick creation of visualization reports.

– Advantage: Tableau offers faster report generation and sharing capabilities.


6. Advanced Analytics:

– Looker: Pre-built code blocks are configurable, allowing for a deeper analytical review of data.

– Tableau: Offers high configurability but lacks pre-built code blocks.

– Advantage: Looker’s configurable code blocks enhance analytical capabilities.


7. Security:

– Looker: Provides an admin panel for security settings and supports 2-factor authentication.

– Tableau: Allows users to protect reports and dashboards but with less granularity than Looker.

– Advantage: Looker offers more robust security features and controls.


8. Mobile Support:

– Looker: Offers a mobile app for data viewing, email, and chat sessions, supporting QR code and biometric login.

– Tableau: Provides a mobile web application for Android and iOS devices.

– Advantage: Looker’s mobile app offers more versatile features for data access and interaction.


9. Pricing:

– Looker: Pricing starts at $5,000 per month, with various business plans available.

– Tableau: Creator license costs $70 per user per month, with viewer licenses at $15 per user per month.

– Advantage: Looker may offer more flexible pricing options for different company sizes and needs.


Selecting the Right BI Software for Your Business


Choosing between Looker and Tableau depends on various factors beyond product features:

– Consider your existing infrastructure, data analytics requirements, and storage preferences (cloud or local).

– Evaluate integration capabilities with existing systems and data sources.

– Assess scalability and flexibility to accommodate future growth and changing business needs.

– Explore user-friendliness and support for non-technical users.

– Examine security features and compliance requirements.


Ultimately, the best BI solution depends on your organization’s unique circumstances, objectives, and priorities. While factors like Google or Salesforce integration may influence the decision, it’s essential to conduct a comprehensive analysis to determine the most suitable BI software for your business’s success.

How to choose between Tableau and Looker –

When faced with the decision between Tableau and Looker for a Business Intelligence (BI) software solution, several essential steps can guide decision-makers towards the most suitable option.


Initially, it’s crucial to pinpoint the specific business needs driving the requirement for BI software. These needs serve as the foundation for outlining the key functionalities and features desired in a BI solution. Each company’s requirements may vary based on factors such as industry, organizational structure, data sources, and analytical objectives.


Once the requirements are identified, decision-makers embark on a process of evaluating the key features and capabilities offered by Tableau and Looker. This comparison involves assessing aspects like data visualization tools, integration capabilities, data modeling options, reporting functionalities, speed of analytics, advanced analytics capabilities, security features, mobile support, and pricing structures.


Moreover, decision-makers may leverage additional research resources, including industry reports, customer reviews, case studies, and expert recommendations, to gain deeper insights into each BI solution’s strengths and limitations. This comprehensive approach ensures a well-informed decision aligned with the organization’s unique needs and objectives.


For those seeking the latest advancements in BI solutions, exploring comprehensive resources like our Business Intelligence Software Buyer’s Guide can provide valuable insights and guidance throughout the decision-making process.


In essence, by systematically evaluating requirements, conducting a thorough comparison of key features, and leveraging relevant research resources, decision-makers can confidently navigate the selection process and choose the BI solution that best aligns with their organization’s goals and objectives.


In conclusion, the decision between Tableau and Looker for a Business Intelligence (BI) software solution hinges on various factors unique to each organization. By meticulously assessing requirements, comparing key features, and conducting thorough research, decision-makers can navigate the selection process with confidence.


Furthermore, staying informed about the latest advancements in BI technology and industry trends is crucial for making informed decisions. Platforms like – provide valuable insights and resources for professionals seeking to enhance their skills and stay abreast of emerging technologies in the realm of data analytics and visualization.


Ultimately, whether your organization prioritizes intuitive data visualization tools, seamless integration capabilities, robust data modeling features, or comprehensive reporting functionalities, the choice between Tableau and Looker should align closely with your specific business needs and objectives.


By leveraging the wealth of information available and conducting a diligent assessment of both Tableau and Looker, organizations can empower themselves to make informed decisions that drive business success and unlock the full potential of their data assets.

FAQs –


1. In terms of data visualization capabilities, how does Looker compare to Tableau?

Looker and Tableau both excel in data visualization, albeit with slightly different approaches. Looker offers dynamic dashboard filters and mapping features, enhancing chart creation. On the other hand, Tableau specializes in visualization dashboards and infographics, providing pre-made templates and a user-friendly wizard feature. While Looker’s emphasis is on flexibility and integration with other BI processes, Tableau prioritizes a wide range of visualization options and ease of use for non-technical users.


2. Can Looker and Tableau be integrated with various data sources?

Yes, both Looker and Tableau offer robust integration capabilities with various data sources. Looker integrates with big data platforms and databases, executing queries without the need for data extraction. Tableau boasts over 200 connectors that can connect to multiple sources, including relational databases, spreadsheets, cloud platforms, and CRM systems like Salesforce. This flexibility enables users to access and analyze data from diverse sources seamlessly.


3. What are the key differences in the user interface and user experience between Looker and Tableau?

The user interface and experience vary between Looker and Tableau. Looker’s interface focuses on providing a clean, customizable workspace with intuitive navigation and dynamic dashboard filters. Conversely, Tableau’s interface emphasizes drag-and-drop functionality and pre-built templates, simplifying the visualization creation process for users. While Looker offers more flexibility in data modeling and dashboard design, Tableau prioritizes ease of use and accessibility for non-technical users.


4. How do Looker and Tableau handle data modeling and preparation?

Looker employs LookML, a data modeling tool that is reusable and flexible, supported by pre-built modeling tools called Looker Blocks. LookML allows for deeper analytical insights and customizable data modeling. In contrast, Tableau utilizes snowflakes and dimensional data models to enhance query performance. While Tableau lacks pre-built code blocks like Looker, it offers high configurability and ease of use in data modeling and preparation, making it accessible to a wider range of users.


In summary, both Looker and Tableau offer powerful data visualization capabilities, seamless integration with diverse data sources, and unique approaches to user interface design and data modeling. The choice between the two ultimately depends on the specific needs and preferences of the organization.

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