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Introducing Dash Enterprise 6.0: Production-Ready Data Apps at Enterprise Scale

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February 26, 2026

Join us for the launch of Dash Enterprise 6, the next evolution of our Kubernetes-native application platform that brings enterprise-grade deployment, security, and operations to Python data teams.

Dash Enterprise 6 transforms how organizations develop, deploy, and operate data applications. Running natively on Kubernetes, it integrates seamlessly with your existing infrastructure, from GitHub and CI/CD pipelines to container registries, observability tools, and cloud identity systems. With 13 deployment steps automated from dependency management to blue-green updates, your teams ship production-ready applications in minutes, not weeks.

Build applications your way. Write Python code directly, or use Plotly Studio's AI-native approach to generate fully functional Dash apps from natural language and data. Both paths lead to the same production-ready applications deployed on Dash Enterprise 6.

In this launch webinar, you'll discover how Dash Enterprise 6 delivers:

  • AI-powered development with Plotly Studio AI-native code generation and Dash Enterprise’s browser-based IDE 
  • Native Kubernetes deployment with automated containerization and orchestration, backup and restore and High-Availability (HA) architecture
  • Secure-by-default architecture with workload identity, network policies, and least-privilege access
  • Enterprise integrations for SSO, Git, observability, and cloud storage
  • Advanced capabilities including scheduled reports, async job queues, and PDF exports
  • Centralized governance with role-based access control and consistent policies at scale

You'll hear directly from enterprise customers at major financial institutions, utilities, and data providers on how they're using Dash Enterprise to deliver mission-critical applications, from field operations supporting hundreds of thousands of users to financial analytics serving multiple jurisdictions across continents.

Whether you're running air-gapped deployments for regulatory compliance, building customer-facing applications at scale, or breaking through data science bottlenecks, this webinar shows you how Dash Enterprise 6 accelerates your journey from code to production while maintaining the security and control your enterprise demands.

Meet the Speaker

Erik Moore

Erik Moore

As Head of Product and Engineering at Plotly, Erik Moore sets the strategic direction for Dash Enterprise, guiding the platform’s evolution to meet the needs of enterprise customers. He works at the intersection of product, engineering, and customer success to shape a roadmap that balances innovation with reliability. With a background as a software developer, Erik brings technical depth and hands-on experience in data visualization and enterprise-grade, customer-hosted solutions.

Mingo Sanchez

Mingo Sanchez

Mingo Sanchez is Team Lead, Sales Engineer at Plotly. After graduating from Bowdoin College with a degree in computer science, he started working with organizations in the master data management and data science spaces. Throughout his career, Mingo has partnered with large financial institutions, life sciences organizations, retail companies, and government agencies to help them better understand their data and more effectively serve their customers. Mingo enjoys building relationships with people to understand their pain points and help them solve their most challenging business and technical problems.

John Allwright

John Allwright

John Allwright leads Marketing at Plotly, where he drives go-to-market strategy for Plotly Studio and champions the emerging "Vibe Analytics" category, bringing AI code generation to data analytics. With over 12 years marketing developer platforms and AI-powered products at Microsoft, Pivotal, VMware, and data platform startups including Astronomer (Apache Airflow) and Decodable (Apache Flink), John helps technical teams adopt transformative technologies. As a former developer turned marketer, he understands the real-world challenges data practitioners face when building analytics solutions.

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