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Looker vs QuickSight

Last Updated: November 18th, 2024

Our analysts compared Looker vs QuickSight based on data from our 400+ point analysis of Business Intelligence Tools, user reviews and our own crowdsourced data from our free software selection platform.

Overview Pricing Benefits & Features Analyst Ratings Comparison Charts User Ratings Analyst Summary Screenshots

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Product Basics

Looker is a web-based analytics solution that offers businesses the ability to explore, discover, visualize and share data insights. Enterprises can view data sources and drill down into data to better understand their business and metrics.

Using a simple proprietary modeling language, this system helps define data relationships while bypassing SQL. It facilitates data literacy and accessibility, irrespective of technical skill levels. It was acquired by Google on June 6, 2019, for $2.9 billion.

Amazon QuickSight is a business intelligence tool that enables organizations to visualize and analyze data, derive insights, and make informed decisions. It empowers users with interactive dashboards, data exploration capabilities, and machine learning-driven insights, making it an ideal solution for businesses seeking to leverage data for better outcomes.

The benefits of Amazon QuickSight include its ease of use, fast performance, and scalability to handle large datasets. Its popular features include natural language querying, automated insights generation, and integration with other AWS services. Compared to similar products, Amazon QuickSight stands out for its affordability, ease of deployment, and robust feature set.

Pricing for Amazon QuickSight is based on a per-user, per-month subscription model. It offers flexible pricing options to accommodate varying business needs, ensuring cost-effectiveness and scalability as organizations grow.

$2,900 Monthly

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$5/User, Monthly

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Product Insights

Real-Time Data: Keep up to date on the most recent numbers through real-time updates to dashboards and other visualizations.
Local Database: Uses an organization’s proprietary database to collect data — no need to rely on parallel data pipelines or data extracts.
Self-Service BI: Explore data through the self-serve function and then refine the automatically generated visualizations. Create custom dashboards to reflect specific KPIs based on the business’ specific needs.
Virtual Schema: Create live connections to over 35 SQL databases through a code-based virtual query-time schema. Keeps data visualizations secure and up-to-date.
Embedded Analytics: Embeddable through SSO, it can deploy into third-party solutions like a CRM or ERP as an embedded iframe or through Javascript. Empowers other software solutions with BI capabilities including reliable data, self-service analytics, actionable insights and intuitive dashboards.

Self-Service BI: Get answers to questions and share insights independently through self-service analysis of business data. Connect to data sources, manipulate values to create visualizations, invite others to collaborate and share dashboards and reports — all without the need to install any application.
Multi-Tenancy: Its multi-tenant architecture with namespaces allows vendors to provide data exploration and dashboarding capabilities for multiple applications at the same time. Host multiple clients and add templates created and shared by dashboard authors to the proprietary visualizations library.
Embedded Analytics: Embed dashboard sessions into proprietary software to enhance business with console analytics. Personalize the appearance of visualizations and reports by adding custom fonts, colors and styles. Set defaults and error handling to match the host application for a cohesive feel.
Report Sharing: Stay informed as to how key metrics are performing by scheduling automatic email updates. Ensure secure access to dashboards and email reports by showing only relevant data through targeted reports.
Flexible Pricing: Save on upfront costs and capacity planning through its p ay-as-you-go pricing model for report consumers — people who view dashboards, but don’t create them.
Mobility: Get data insight and forecasting summaries on-the-go through its mobile version, available on both iOS and Android. Drill down into mobile-optimized dashboards and reports for in-depth analysis and filter to view specific metrics, even when away from the office. Share results with others and get email alerts for changes in business data as they happen.
Automate Deployments: Deploy applications at scale, keeping them online for continued access while minimizing downtime. AWS CodeDeploy provides automated app deployments to multiple cloud compute services, such as Amazon EC2, AWS Fargate, AWS Lambda, and on-premise servers. Seamlessly integrates with continuous delivery process pipelines, such as AWS CodePipeline, GitHub and Jenkins.
Promote Data Literacy: Identify key metrics, perform what-if analysis through simple point-and-click actions, discover hidden trends and generate forecasts — without needing any technical skills. Generates dashboard summaries in easy-to-understand language to enable shared understanding of data insights.
Scalable: Its serverless architecture makes it easily scalable, ensuring fast loading of dashboards even during peak traffic. Scales as the organization grows to take on larger loads — no need to set up dedicated servers.
Data Security: Its Enterprise version provides additional security features through permissions-based access to AWS data, row level security, SSO and data encryption. It is FedRamp, HIPAA, PCI PSS, ISO and SOC compliant, keeping with industry best practices.

Automated Modeling: Connects to relational databases and automatically generates models from the database schema.
Intuitive Visualizations: Generates visualizations in real time directly from the specified data source. Choose from an expansive library of visualization options like bar graphs, pie charts, Sankey diagrams, spider web charts, sunburst graphs, chord diagrams, heatmaps, funnels, treemaps and many more.
Time Zone Handling: Incorporates data seamlessly into the visualization, regardless of what time zone it is coming from.
LookML Data Modeling Language: Create scalable, reusable data models through the proprietary SQL-based data modeling language LookML.
Pre-Built Analytics Code: Use its Blocks feature as a starting point for building data analytics models with customizable code blocks. Includes optimized SQL patterns, custom visualization options, pre-built data models and more.

Data Connectivity: Connect to a multitude of cloud-based and on-premise data sources such as Salesforce, JIRA, Github, Teradata, MySQL, SQL Server, Postgres and many more, or upload data from Excel, JSON, CSV and Presto files.
Integrations: Perform predictive data analysis by integrating Amazon Sagemaker ML-based data models with its supported data sources, such as S3, Athena, Redshift, as well as third party sources that include Salesforce and JIRA, among others. Easily integrates with BI tools such as Domo and Tableau for data querying through an intuitively similar SQL interface.
Data Visualization: Create interactive visualizations and reports by choosing from a rich library of graphs, charts and tables. Build dynamic dashboards by interacting with data in real time through drag-and-drop, drill-down and filtering options.
Reporting: Its Enterprise edition provides ad-hoc as well as scheduled reporting to share targeted reports on a daily, weekly or monthly basis. Subscribe to receive reports via email. Creates a custom snapshot of the report based on individual data permissions.
In-Memory Engine: Perform calculations and analyses at the speed of thought by querying through its super-fast parallel in-memory calculation engine, SPICE. Built from the ground up, it prepares data faster by replicating it in memory and updates in real-time as the underlying data changes.
Dashboards: Create data dashboards with 28 supported charts, such as filled maps, histograms, funnel charts, stacked area charts, waterfall charts and boxplots, as well as tables and pivot tables. View information based on business context by sorting on fields not shown in the visualization. Provide report readers with on-sheet controls to slice and dice data by filtering on fields. Offers multiple report layout customization options that include adding drop-downs with single-select or multi-select sorting.
ML-Based Insight: Get in-depth data insights through its out-of-the-box ML and NLP capabilities. Perform queries on data in seconds in simple language through its natural language attribute, Q. It learns from data patterns to provide accurate predictions based on historical trends. Detect anomalies and variations in data aggregates through scheduled anomaly detection.
Localization: Available as a global solution with support for 10 major languages: English, German, Spanish, French, Italian, Portuguese, Japanese, Korean, Simplified Chinese, and Traditional Chinese.

Product Ranking

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#80

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Analyst Rating Summary

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User Sentiment Summary

88%

of users recommend this product

Looker has a 'great' User Satisfaction Rating of 88% when considering 1836 user reviews from 5 recognized software review sites.

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Synopsis of User Ratings and Reviews

Reporting: Looker features strong reporting features that offer a degree of granularity and scheduling that 100% of users who mention reporting evaluate as a strong benefit.

Support: Of the users who say they’ve contacted customer support, 95% say the team’s quick and informative responses are a plus.

Data Accessibility: All users who mention accessibility to data say Looker does this well, distributing insights to employees across departments and teams with ease, with 100% of users mentioning this feature believing it is a benefit.

Self-Service Analytics: QuickSight empowers business users to create and customize visualizations, dashboards, and reports without relying on IT or data scientists.

Cloud-Based Platform: QuickSight's cloud-based architecture eliminates the need for costly on-premise infrastructure and provides seamless access from anywhere with an internet connection.

Scalability and Performance: QuickSight handles large datasets efficiently, allowing users to analyze vast amounts of data in real-time.

Easy Integration: QuickSight seamlessly integrates with popular data sources, including Amazon Redshift, Amazon Aurora, and Salesforce, enabling users to access and analyze data from various systems.

Machine Learning Capabilities: QuickSight leverages machine learning algorithms to provide predictive analytics, anomaly detection, and automated insights, empowering users to uncover hidden patterns and make data-driven decisions.

Collaboration and Sharing: QuickSight facilitates collaboration among teams by allowing users to share dashboards, reports, and insights securely.

Learning Curve: About 74% of users who touch on the platform’s ease of use say that the confusing documentation, lack of training opportunities and difficulty of using programming language make Looker a tough tool to pick up as a beginner.

Setup: Of the users who mention implementation, 81% say that setting up the platform is difficult, with integrations not being as plug-and-play as competitors and assistance from IT necessary to the setup process.

Speed: Approximately 87% of users who comment on the platform’s speed say that it is slow to render certain queries and often takes a while to load.

Functionality: About 78% of users who talk about Looker’s features say that they are left wanting many functions and find the ones that it does have limited in customization or too complex to use easily.

Pricing Structure: Complicated pricing model that can lead to unexpected costs for advanced features and usage.

Limited Customization: Pre-built dashboards and visualizations may not fully meet specific business requirements, limiting customization options.

Data Connectivity: May not seamlessly integrate with all data sources, requiring additional effort for data preparation and ingestion.

Limited Advanced Analytics: Lacks certain advanced analytical capabilities, such as predictive modeling and machine learning algorithms, which may be essential for deeper insights.

User Interface: Some users find the user interface to be cluttered and not as intuitive as other BI tools, impacting the ease of use.

Looker is a forerunner in the business intelligence field for a reason; it generates reports that include easy sharing via link, automatic scheduling and a level of granular detail that allows for deeper analysis below the surface. It excels in its filter and drill-down features and creates unique URLs when users make changes to data, leading to enhanced sharing. However, one of its biggest strengths could also be considered one of its biggest weaknesses: its proprietary programming language, LookML which is used to construct SQL queries in the platform. While a flexible and powerful data querying language, of course, LookML isn’t the most accessible to non-technical users, which means that Looker requires an IT or data team to access its full capabilities and has a steep learning curve. Users also note that its data visualizations, while simple and easy to understand, are quite basic and lacking in customization options, particularly in comparison to competitors. Some users say that it may be more appropriate for internal reporting than presentation to shareholders and end-users because of its bare-bones visualization options. However, Looker truly shines when used by enterprises, with its scalability and data accessibility making it a stellar solution that can align departments and provide thousands of users access to data insights. Its price point reflects this, with its pricing being prohibitive to startups as about 88% of users who comment on its cost remark. Overall, Looker is a solid pick for larger businesses that have a team of power users who can maximize its functionality and set it up to deliver to employees across an entire organization.

Amazon QuickSight has received positive user reviews for its ease of use, intuitive interface, and quick data visualization capabilities. Users find it simple to connect to data sources, create dashboards, and generate insights. The drag-and-drop functionality and pre-built templates make it accessible to users of all technical skill levels. QuickSight's strengths include its integration with other Amazon Web Services (AWS) products, such as Amazon Redshift and Amazon S3, allowing for seamless data analysis. It also offers advanced features like machine learning-powered insights and natural language querying, providing users with deeper analytical capabilities. Compared to similar products, QuickSight is praised for its cost-effectiveness and scalability. Users appreciate its pay-as-you-go pricing model and the ability to handle large datasets without performance issues. However, some users have expressed concerns about the limited customization options and the lack of certain advanced features found in competing products. Overall, Amazon QuickSight is well-suited for businesses and organizations looking for an easy-to-use and affordable business intelligence solution. Its intuitive interface, integration with AWS products, and scalability make it a valuable tool for data visualization, analysis, and decision-making.

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FAQ

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