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Key features include interactive dashboards, powerful data exploration, and integration with many data sources. Typical users are business analysts, data scientists, and non-technical business users.

Key features include built-in AI capabilities, Excel integration, and custom data connectors. Typical users are data analysts, business intelligence professionals, and Excel users familiar with Microsoft ecosystem.

Key features include associative data modeling, in-memory processing, and self-service BI. Typical users are business users, data analysts, and IT professionals.

Key features include real-time data visualization, cloud-based collaboration, and custom app development. Typical users are CEOs, sales leaders, and operations managers.

Key features include interactive analytics, AI-driven insights, and a web-based drag-and-drop interface. Typical users are business analysts, dashboard designers, and IT experts.

Key features include easy sharing and collaboration, connectors for Google services and other databases, and customizable reports. Typical users are digital marketers, small business owners, and data journalists.

Key features include a web-based interface, LookML models for describing data, and custom visualization types. Typical users are data analysts, business intelligence teams, and data-driven companies of all sizes.

Key features include AI-powered assistance, collaborative analytics, and embedding options. Typical users are small to medium-sized businesses, marketing teams, and operational managers.

Key features include AI-driven insights, natural language query, and streaming analytics. Typical users are scientists, business analysts, and corporations requiring advanced analytics.

Key features include interactive reporting, advanced analytics with SAS language, and mobile BI capabilities. Typical users are statistical analysts, large enterprises with advanced analytics needs, and healthcare organizations.

Key features include comprehensive data integration, analytics platform, and embedded analytics. Typical users are IT developers, business analysts, and data engineers in need of a complete data solution.

Key features include real-time dashboards, embedded analytics, and automation of data retrieval. Typical users are startups, SMEs, and marketing agencies.

Key features include extensive chart options, live data support, and JavaScript integration. Typical users are developers, product managers, and companies wanting to add interactive charts to web and mobile applications.

Key features include compatibility with any back-end database, accessibility features, and responsiveness for mobile devices. Typical users are web developers, designers, and any business requiring custom and interactive chart capabilities in their applications.

Key features include easy creation of infographics and reports, a drag-and-drop editor, and social sharing capabilities. Typical users are content marketers, media companies, and educators.

Key features include HTML5 based charting, open-source availability, and a small footprint. Typical users are developers interested in creating interactive graphs using HTML5 canvas, students, and businesses with basic data visualization needs.

Key features include fully customizable dashboards, self-service analytics, and scalable architecture. Typical users are large organizations, BI professionals, and enterprises looking for comprehensive BI and analytics suite.

Key features include interactive web-based visualizations, support for Python, R, and Matlab, and Dash framework for building analytical web applications. Typical users are data scientists, engineers, and analysts.

Key features include ease of use without coding, chart, and map creation, and responsiveness for all devices. Typical users are journalists, NGOs, and businesses needing quick and attractive visuals without a steep learning curve.

Key features include an open-source approach to data visualization, the ability to work with vector graphics, and usage of D3.js layout. Typical users are designers and developers who prefer custom visual solutions, as well as academic researchers.

Key features include network analysis and visualization, real-time interaction, and support for large networks. Typical users are sociologists, biologists, and data analysts focusing on complex relational data.

Key features include handling huge datasets, interactive exploration of data and support for annotations. Typical users are developers, researchers, and businesses with a need for interactive time-series visualizations.

Key features include hyperintelligence cards, federated analytics, and cloud support. Typical users are enterprises requiring a robust BI tool, data engineers, and analytics experts.

Although not strictly a visualization tool, it offers numerical computing with Python and can be used in conjunction with other libraries to create visualizations. Typical users are researchers, scientists, and developers working with numerical data in Python.