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In this presentation and live demo, Chanin Nantasenamat (a.k.a. @DataProfessor), Senior Developer Advocate at Streamlit, walks through the full process of creating and deploying interactive dashboards using Python and Streamlit. You’ll learn how to: • Think about dashboard design as a creative, iterative process • Clean and explore data through EDA • Build a Streamlit app with interactive filters and charts • Walk through and understand the code behind the dashboard • Deploy your app using Streamlit Community Cloud • Handle performance and scalability with large datasets • Add new features and connect to databases like Snowflake Chanin also shares how tools like ChatGPT can help generate starter code, and discusses the evolving role of data visualization in modern analytics. Whether you’re new to Streamlit or looking to take your data apps to the next level, this session offers both a strategic overview and practical demo. 🔧 Tools discussed: @streamlitofficial, Python, Pandas, @altair_inc, @GitHub, @SnowflakeInc, ChatGPT 00:00 Introduction and Greetings 00:25 Crafting a Dashboard in Python with Streamlit 01:24 The Importance of Data Visualization 04:31 Exploratory Data Analysis (EDA) 05:39 Data Collection and Cleaning 07:25 Feature Engineering and Machine Learning 15:53 Building Interactive Dashboards 18:41 Deploying Streamlit Apps 24:00 Streamlit Development Environment 25:48 Creating and Deploying a Dashboard App 32:17 Real-Time Updates and Data Filtering 33:59 Exploring the Code Structure 36:47 Optimizing Performance and Handling Large Data 43:01 Adding New Features and Customizations 47:53 Connecting to Databases and Deployment Options 53:03 Conclusion and Final Thoughts