QuickSight Reviews & Pricing

by Amazon Web Services | Founded 2015, Seattle, WA

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What is QuickSight?

Industry Specialties: Serves all industries

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.

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QuickSight Pricing

Based on our most recent analysis, QuickSight pricing starts at $5 (Per User, Monthly).

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Starting From: $5
Pricing Model: Per User, Monthly
Free Trial: Yes, Request for Free

Training Resources

QuickSight is supported with the following types of training:

Documentation
In Person
Live Online
Videos
Webinars

Support

The following support services are available for QuickSight:

Email
Phone
Chat
FAQ
Forum
Help Desk
Knowledge Base
Tickets
Training
24/7 Live Support

QuickSight Benefits and Insights

Why use QuickSight?

Key differentiators & advantages of QuickSight

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.

Industry Expertise

Amazon Quicksight provides data analytics capabilities to clients from diverse industries around the world. These include risk management, sports, mining, construction, manufacturing, automotives, software development, hospitality, marketing and many more.

Synopsis of User Ratings and Reviews

Based on an aggregate of QuickSight reviews taken from the sources above, the following pros & cons have been curated by a SelectHub Market Analyst.

Pros

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.

Cons

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.

Researcher's Summary:

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.

Key Features

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.

Limitations

At the time of this review, these are the limitations according to user feedback:

Allows pivot table calculations only on non-aggregated values
Doesn’t authenticate users of Active Directory, so they are limited to reading the visualizations
Its calculation engine limits the number of rows that can be added to its datasets
Can’t access two embedded dashboards from two different Amazon Quicksight accounts within the same browser session
Can’t send scheduled emails to groups with more than 5,000 members

Suite Support

Before emailing support, access technical documentation, the knowledge center, support forums, whitepapers, videos, user guides, blogs, articles and tutorials available on the vendor’s website for self-service issue resolution and answers to queries.

For no additional cost, all AWS customers can avail basic support that includes access to the resource center, service health dashboard, product FAQs, discussion forums and support for health checks. Sign up for the Developer Support plan for 24/7 access to customer service, with email support during business hours. Subscribers to the Business Support plan and above have 24/7 access to support via email, phone and chat, with the Personal Health Dashboard, AWS Trusted Advisor and third-party software support. The Enterprise Support license provides a dedicated Technical Account Manager (TAM) for onboarding and subsequent support, as well as access to AWS subject matter experts.

Email: Available to licensed subscribers only.

Phone: Direct phone support isn’t available. Phone callbacks are available to licensed subscribers only.

Training: Register for free, self-paced instructor-led courses, either virtually or in-person, or attend webinars, online or onsite. Or, sign up for self-paced paid courses from digital training providers such as edX and Coursera. Opt for AWS Partner training as a business or technical professional, or get certified as an associate, a professional or a cloud computing specialist with AWS.

Tickets: Create a case from the Support Center through a subscriber account.