In today's fast-paced data environment, the ability to quickly transform raw data into actionable insights is crucial.
This session demonstrates how Plotly AI revolutionizes the dashboard development process by enabling natural language-driven creation of sophisticated data applications. The demonstration will follow a real-world workflow:
- Data Ingestion & Exploration: We'll begin with raw data and use Plotly AI's natural language interface to explore the dataset.
- Visualization Creation: Through simple prompts, we'll generate interactive visualizations that update in real time.
- Dashboard Assembly: We'll demonstrate how to assemble individual visualizations into a cohesive, interactive dashboard.
- Deployment & Sharing: Finally, we'll show how the resulting application can be easily deployed and shared with stakeholders
Throughout the demonstration, we'll highlight how Plotly AI:
- Generates Python code automatically from natural language descriptions - Suggests optimal visualization types based on data characteristics
- Handles real-time data updates
- Enables rapid iteration through conversational refinement
Key Takeaways:
- How to leverage AI-assisted tools to accelerate the dashboard development process
- Techniques for building real-time data applications without extensive coding
- Best practices for translating business requirements into visualization specifications
-Strategies for deploying and sharing interactive data applications
Speaker:
Mingo Sanchez is a Senior 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.
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