New Capability of Amazon Q in QuickSight Makes Every Employee Their Own Data Analyst

Rhea-AI Summary

Amazon Web Services (AWS) has announced the general availability of a new capability for Amazon Q in QuickSight, enabling employees to perform expert-level data analysis using natural language. This AI-powered feature allows users to analyze data without specialized skills, performing complex analysis up to 10x faster than spreadsheets.

The tool empowers employees to dive deep into company data, uncover trends, and make recommendations through natural language queries. Used by over 100,000 customers including startups and Fortune 500 companies, Amazon QuickSight combines structured data from warehouses with unstructured data from documents, emails, and messages.

Major companies like Availity, BMW Group, and various Amazon teams are already implementing this technology. BMW Group uses it to manage vehicle inventory and investigate supply chain bottlenecks, while Availity employs it to streamline healthcare information analysis. The system maintains high security standards, ensuring customer data is never used to train underlying models.

Positive

• Launch of new AI capability that could drive additional revenue through QuickSight adoption
• Significant customer base of over 100,000 clients including major enterprises
• Technology performs complex analysis 10x faster than traditional methods
• Successfully implemented by major clients like BMW Group and Availity

Negative

• None.

Insights

Cloud Technology Analyst

AWS's general availability release of Amazon Q in QuickSight's scenarios capability represents a strategic enhancement to their business intelligence portfolio. This AI-powered natural language interface for data analysis addresses a significant market pain point - the technical barriers that prevent non-specialists from performing complex data analysis.

The technology allows employees to bypass the traditional bottlenecks of waiting for data analysts or struggling with spreadsheets, potentially accelerating analysis workflows by up to 10x according to AWS. What's particularly notable is the conversational approach to scenario modeling and what-if analysis, tasks traditionally requiring specialized expertise.

From a competitive standpoint, this positions QuickSight more strongly against Microsoft's Power BI and Tableau in the $20+ billion business intelligence market. While all major platforms are integrating generative AI capabilities, Amazon's implementation focuses on democratizing advanced analytical capabilities rather than just enhancing visualizations or automating basic tasks.

The enterprise-grade security claims - specifically that customer data and interactions aren't used to train underlying models - addresses a key enterprise concern about generative AI adoption. With 100,000+ existing QuickSight customers and named implementations at organizations like BMW Group and Availity, this appears to be production-ready technology with actual business use cases, not merely experimental capabilities.

Enterprise Software Investment Analyst

This product enhancement strengthens AWS's analytics portfolio, but investors should maintain measured expectations about near-term financial impact. Amazon QuickSight operates in the growing BI market, where differentiation through AI could improve competitive positioning against established players like Microsoft, Tableau/Salesforce, and Google.

The business value proposition of democratizing data analysis is compelling - reducing analytical bottlenecks while enabling faster decision-making across organizations. Reference customers like BMW Group implementing the technology for inventory management demonstrates potential enterprise-level use cases with measurable efficiency gains.

While the release expands AWS's AI capabilities portfolio, QuickSight represents a relatively small component of AWS's $90+ billion annual revenue. The enhancement will likely improve QuickSight's competitiveness and retention but probably won't materially impact Amazon's overall financial performance in the near term given the company's scale.

The product aligns with Amazon's broader strategy of embedding generative AI across its cloud service portfolio to enhance functionality and maintain competitive positioning. As organizations increasingly seek to make data-driven decisions without expanding specialized data teams, solutions like this address a growing market need. Long-term, such productivity-enhancing tools could drive increased AWS adoption and help maintain AWS's cloud market leadership position.

Employees can use natural language to perform expert-level data analysis, ask what-if questions, and get actionable recommendations, helping them unlock new insights and make decisions faster

SEATTLE--(BUSINESS WIRE)-- Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), today announced that Amazon Q in QuickSight unlocks the ability for any employee to perform expert-level data analysis using natural language. The new scenarios capability of Amazon Q in QuickSight, now generally available, uses an advanced artificial intelligence (AI) agent to empower all employees to engage via natural language to perform data analysis without any specialized skills or expertise. Amazon Q in QuickSight is a generative AI assistant that helps employees get insights faster and make better decisions using Amazon QuickSight, AWS’s AI-powered business intelligence (BI) service.

Figure 1 The scenarios capability of Amazon Q in QuickSight

• Now any employee can use natural language to dive deep into their data and receive expert guidance that helps them uncover hidden trends, make recommendations for their organization, and identify new business opportunities to explore next.
• The new AI capability for Amazon Q in QuickSight also accelerates productivity for data analysts, helping them build elaborate models and formulas using natural language and perform complex analysis up to 10x faster than spreadsheets.
• Amazon Q in QuickSight is built to meet the highest levels of security and privacy and never uses customer data or inputs and outputs to train the underlying models.
• Employees at companies like Availity and the BMW Group, as well as other businesses across Amazon, are using the scenarios capability of Amazon Q in QuickSight to transform decision-making.

“We are at the beginning of a workplace transformation driven by agents, and Amazon QuickSight is pioneering how this technology can break down the technical barriers between employees and their data,” said Dilip Kumar, vice president of Amazon Q Business, AWS. “With the new scenarios capability, everyone becomes their own data analyst who can dive deep into their company data, helping them unlock insights, make better decisions, and explore countless possibilities faster than ever before.”

Used by more than 100,000 customers at companies ranging from startups to the Fortune 500, including Docebo, GoDaddy, and the National Football League, Amazon QuickSight powers unified BI capabilities, including interactive dashboards, paginated reports, and embedded analytics, that help employees make better decisions. Amazon Q in QuickSight brings generative AI to business intelligence, transforming how employees interact with data through conversational capabilities like AI-powered executive summaries, a context-aware, multi-visual data question-and-answer experience, and customizable, interactive data stories. Unlike traditional BI solutions that only allow users to analyze data from databases, data warehouses, and data lakes, Amazon Q in QuickSight allows users to bring all their enterprise data into the decision-making process, combining structured data stored in data warehouses and unstructured data from documents, webpages, emails, images, messages, and more.

An AI capability that revolutionizes how employees work with data

Timely access to the right data and insights can help employees make faster, more informed decisions that lead to better business outcomes. However, accessing those insights via legacy BI tools and dedicated analysis tools like spreadsheets often requires specialized skills or help from a business analyst to select the right data, understand it, determine the analytical approach, perform the analysis, and interpret it to identify actionable recommendations. Most organizations depend on dashboards and reports for insights, which is often insufficient, or on manually manipulating data in spreadsheets, an error-prone process that can take days to complete. With the new scenarios capability of Amazon Q in QuickSight, every employee can perform their own advanced data analysis tasks in minutes through a simple conversation—no specialized expertise required. For example, a marketer can evaluate the impact of a new subscription program, or a warehouse manager can find new ways to optimize operations.

To get started, employees select information from a QuickSight dashboard or upload their own spreadsheet to QuickSight and start asking questions like, “What drove the month-over-month increase in revenue in Belgium?” Amazon Q then automatically analyzes and visualizes the data, providing actionable recommendations based on their inquiry. Whether an employee needs to forecast sales trends, optimize an operational process, or determine how to improve a marketing campaign, the AI capability breaks down data analysis into a series of easy-to-understand, executable steps, making it possible to build sophisticated analyses in minutes. With the new capability, employees can easily move beyond basic observations to model solutions, compare alternatives, and answer exploratory questions like, “What if we extended our free trial period?” or “How would this impact conversion rates?” or “What if we could reduce customer churn by 20%?” This makes it faster and easier to explore new possibilities and compare alternatives side-by-side to better inform decision-making.

Working with natural language and an intuitive user interface, employees can perform advanced data analysis with just a few clicks, eliminating errors associated with manual data manipulation or moving information across spreadsheets. Employees can also easily access, modify, extend, and reuse previous analyses to quickly adapt to changing business needs or revisit past analyses when data changes. As a part of Amazon Q in QuickSight, the scenarios capability is built to meet enterprise-grade security and privacy standards. No data or Amazon Q in QuickSight inputs or outputs are used to improve the underlying models used by Amazon Q.

Amazon Devices product marketing team uses the scenarios capability of Amazon Q in QuickSight to find new ways to reach developers creating Amazon Appstore applications, encouraging them to build novel Appstore integrations and increase the reach of their products. The team tracks many KPIs to measure the health of their entire business, from usage and adoption to customer satisfaction and pain points. For example, today they have a QuickSight dashboard that shows trends of support tickets coming into their queue—with key metrics such as ticket volume, status, and age. However, these metrics alone did not capture the vast amount of contextual information that was included in the ticket descriptions. Now, with the new capability in Amazon Q in QuickSight, the Appstore team is able to go much deeper and pull out customer insights from the descriptions of these tickets in minutes, enabling them to better support their customers, reduce time spent troubleshooting, and increase overall customer satisfaction.

Availity, one of the largest real-time health information networks in the U.S., increasingly uses QuickSight as the one-stop-shop for their business metrics and reporting. While QuickSight dashboards provide a comprehensive view of the business overall, many employees have questions unique to their role, like, “What is the Tax ID for these five providers?” or “Can you show me how many claims have been filed with this doctor?” that require a level of detail beyond the dashboards. With the scenarios capability of Amazon Q in QuickSight, every employee can conduct their own analysis using natural language, allowing them to get the answers they need faster while reducing the burden on Availity analysts, so they can prioritize more strategic tasks.

The BMW Group is a leading manufacturer of premium automobiles and motorcycles, utilizing Amazon QuickSight to efficiently manage inventory across thousands of vehicles, each characterized by numerous attributes. Previously, when associates needed to investigate complex issues such as supply chain bottlenecks or identify factors contributing to aging vehicle stock, they had to manually sift through dashboards and spreadsheets, consuming significant amounts of time. Now, leveraging the new scenarios capability of Amazon Q in QuickSight, BMW Group’s teams can perform these detailed investigations within minutes by simply using natural language queries and swiftly modeling new scenarios. Given the promising early results, the BMW Group is currently evaluating to extend this advanced capability across various business units, enabling faster, data-driven decisions that enhance operational efficiency.

The scenarios capability of Amazon Q in QuickSight is generally available today. To learn more, visit:

• The AWS What’s New post for details on today’s announcement.
• The Amazon Q in QuickSight page to learn more about the capability.
• The Amazon Q in QuickSight customer page to learn more about how companies are using Amazon Q in QuickSight.

About Amazon Web Services

Since 2006, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud. AWS has been continually expanding its services to support virtually any workload, and it now has more than 240 fully featured services for compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), mobile, security, hybrid, media, and application development, deployment, and management from 114 Availability Zones within 36 geographic regions, with announced plans for 12 more Availability Zones and four more AWS Regions in New Zealand, the Kingdom of Saudi Arabia, Taiwan, and the AWS European Sovereign Cloud. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—trust AWS to power their infrastructure, become more agile, and lower costs. To learn more about AWS, visit aws.amazon.com.

About Amazon

Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. Amazon strives to be Earth’s Most Customer-Centric Company, Earth’s Best Employer, and Earth’s Safest Place to Work. Customer reviews, 1-Click shopping, personalized recommendations, Prime, Fulfillment by Amazon, AWS, Kindle Direct Publishing, Kindle, Career Choice, Fire tablets, Fire TV, Amazon Echo, Alexa, Just Walk Out technology, Amazon Studios, and The Climate Pledge are some of the things pioneered by Amazon. For more information, visit amazon.com/about and follow @AmazonNews.

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FAQ

What is the new capability announced for Amazon Q in QuickSight (AMZN)?

Amazon Q in QuickSight now offers natural language processing capabilities that allow any employee to perform expert-level data analysis without specialized skills, working up to 10x faster than traditional spreadsheets.

How many customers currently use Amazon QuickSight (AMZN)?

Amazon QuickSight is used by more than 100,000 customers, ranging from startups to Fortune 500 companies, including Docebo, GoDaddy, and the National Football League.

What security measures does Amazon Q in QuickSight (AMZN) implement?

The system is built to meet enterprise-grade security and privacy standards, and explicitly does not use customer data or inputs/outputs to train its underlying models.

How is BMW Group utilizing Amazon Q in QuickSight (AMZN)?

BMW Group uses Amazon Q in QuickSight to manage inventory across thousands of vehicles, investigate supply chain bottlenecks, and identify factors affecting aging vehicle stock through natural language queries.