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Dive into the world of agentic analytics with the Phidata Agent library and DuckDB! In this video, we'll build a Streamlit app designed for a tennis commentator, showcasing how to leverage Phidata tools for data analysis and uncover meaningful insights. Whether you're new to Phidata or experienced in data engineering, this walkthrough offers practical examples to enhance your skills. Resources: 🟡 Code - https://github.com/mneedham/LearnData... 🟡 DuckDB tool - https://docs.phidata.com/tools/duckdb 🟡 Streamlit - https://docs.phidata.com/tools/duckdb Timestamps: 0:00 - Introduction to ad hoc analysis with Phidata and DuckDB. 0:07 - Exploring the concept of agentic analytics. 0:20 - Quick recap of Phidata's agent structure and its components. 0:43 - Building a tennis commentator app with Streamlit and DuckDB. 1:07 - Setting up tools like GPT-4 and DuckDB for real-time analytics. 1:24 - Understanding tools and toolkits in Phidata. 1:48 - Introduction to DuckDB toolkit and its capabilities. 2:34 - Key functions of DuckDB, including SQL queries and table descriptions. 3:14 - Walkthrough of the Streamlit app's code structure. 3:43 - Managing session states in Streamlit for chat-based applications. 4:48 - Exploring data from a tennis ranking dataset using DuckDB. 6:00 - Running queries and retrieving player ranking statistics. 7:05 - Advanced queries: analyzing player ranking transitions and trends.