Streamlit for Snowflake Masterclass Hands-On

Build data-driven Streamlit apps from scratch with front-end architecture, output and input controls, and interactive charts. Connect to Snowflake, deploy in Streamlit on Snowflake and share via data marketplace.

Build a simple hierarchical data viewer in python by loading a csv with pandas, creating edges in a graphviz digraph, and previewing url-encoded graphs via web browser.

Convert the hierarchical data viewer into a Streamlit web app by building an interface with a data frame and Graphviz charts, then run and deploy via Streamlit for dashboards.

Explore building interactive hierarchical data charts in Streamlit using Plotly, including treemap, icicle, sunburst, and sankey visuals, while mastering Streamlit output controls and data frames.

Learn to organize charts in streamlit using expander, tabs, containers, columns, and sidebar; render figures with st.plotly_chart inside these layouts, and understand their static behavior and with-syntax options.

Convert tabular data to json, xml, and yaml to reveal hierarchical structures and animations in Streamlit. Build collapsible trees and animated network graphs with Streamlit components for Snowflake deployments.

Enhance the original data viewer by adding Streamlit tabs and a sidebar select box to switch between data frame, graph, and code, deriving child and parent relationships and ID views.

Explore streamlit input controls and how to upload csv files with the file uploader. Learn how to handle csv data with string io and how onchange events drive page reruns.

Discover how to cache data between Streamlit page reruns with cache data or cache resource, using st.form and a submit button to reuse dataframes and avoid reloading.

Discover how to preserve file lists across streamlit page reruns using session state, capture actual file names from uploads, and manage default and loaded files.

Finalize the hierarchical data viewer as a Streamlit web app by integrating animated charts, json, xml, yaml formats, and graphviz and d3 visualizations, including collapsible tree and dendrograms, across tabs.

Deploy your local Streamlit app to the Streamlit community cloud by saving files to GitHub and deploying, showcasing data science apps like object detection and real estate analytics.

Deploy your local web app to Streamlit Cloud by pushing to GitHub, connecting with Google, and publishing to a live, shareable url.

Explore how Streamlit manages per-browser session state in multi-user apps and how caching can affect all users. Hash cached file content with a generated UUID-based session id to isolate caches.

Build a single-page streamlit data analysis app to explore brazilian real estate data from a csv, with side-by-side matplotlib and seaborn charts of price per square meter and strip plots.

Learn to build a CNN-based object detection app with Streamlit, using YOLO weights and OpenCV, featuring a one-page interface, progress bars, and data caching for interactive machine learning demos.

Connect Streamlit apps to Snowflake using SnowSQL, the Snowflake Python Connector, and Snowpark for Python, then deploy with Streamlit Cloud, and leverage UDFs, procedures, and data lineage viewers.

Sign up for a free Snowflake trial, select enterprise on AWS, create a database, load a local CSV into a new table, and inspect the table via the web UI.

Connect to snowflake with the SnowSQL CLI using the account locator and credentials, optionally via environment variables, then run queries from the command line and manage the database and schema.

Connect to Snowflake with the Python connector and install snowflake-connector-python. Create a client-side connection, run SQL via a cursor, and fetch results or load into a pandas data frame.

Explore how Snowpark for Python moves business logic to the database using data frames, server-side execution, stored procedures, and user defined functions.

Build complex declarative queries using the Snowpark data frame API, starting from a session and tables, then join, aggregate, and execute with collect or show to run on Snowflake.

Learn to move complex Python logic into a Snowpark stored procedure, using the sproc decorator and session object to compute new salaries near the data instead of every client query.

Demonstrates connecting to Snowflake from Streamlit using Snowflake connector for Python and Snowpark with a session. Explains caching, secrets handling, and building a multi-page Streamlit app with a Snowflake connection.

Connect the hierarchical data viewer to Snowflake using Snowpark and the SnowSQL config, switch between csv and database sources, and render interactive hierarchies with a tree and network visualizations.

Enhance the hierarchical data viewer with recursive SQL in Snowflake, using recursive CTEs or views to show each employee's managerial path, with indentation and level-based formatting, and runtime table support.

Deploy the connected hierarchical data viewer to Streamlit Cloud, enabling users to connect to their own Snowflake accounts via a form, and separating local from remote sessions with caching.

Explore a hierarchical metadata viewer in Streamlit that visualizes object dependencies and data lineage from Snowflake, using a multi-page app with a pages folder and graph visualizations.

Create a Streamlit entity-relationship diagram viewer for Snowflake, visualizing PK/FK relationships from databases like Chinook and Indian reserves, using a model extractor and DBeaver.

Create a sentiment analysis app for IMDb reviews using Snowpark, Streamlit, and Snowflake. Train a binary classifier with SVM, then deploy a stored procedure and a UDF for real-time predictions.

Learn to connect Streamlit apps with Snowflake and OpenAI by building a chat-powered data assistant that generates and executes Snowflake SQL queries using ChatGPT.

Build a ChatGPT powered agent that answers questions about selected web pages by creating a local index with llama index, and running a Streamlit app with OpenAI integration.

Explore two Snowflake frameworks, Streamlit apps and the native app framework, deploying Python web apps to virtual warehouses via stages and Streamlit objects for sharing with consumers.

Create and deploy a Streamlit app in Snowflake, configure database, schema, warehouse, and stage, generate and run a Streamlit object, and test locally then deploy to Snowflake.

Deploy and test a hierarchical data viewer as a Streamlit app in Snowflake, showcasing table views, Plotly charts, and graceful handling of not supported features.

Deploy the metadata viewer as a Streamlit app in Snowflake, handling object dependencies and data lineage with a multi-page interface loaded via the deployment script.

Create a multi-page streamlit app with Vega-Lite charts to visualize marketplace data from snowflake, organizing charts into separate pages and using a deploy script.

Learn to build a multi-page streamlit app using snowpark for python and altair charts, with data loading, dataframe transformations, and sidebar-driven queries.

Build a data science workflow with snowflake, snowpark, and streamlit by training a linear regression model and predicting with a UDF.

Deploy the hierarchical metadata viewer as a Snowflake native app with an application package, consumer script, manifest, and private stage. Grant privileges and publish to accounts or the marketplace.

Deploy the hierarchical data viewer as a Snowflake native streamlit app, using secure views and a show path stored procedure to share hierarchies with consumer accounts in your organization.

Enrich ip address data by building a Snowflake native app with Streamlit, loading ip2location csv data, and presenting enriched results via a callback.

Explore installing and running a free Snowflake native app from the marketplace. Learn how privileges and compute credits affect costs on your account when using the Ops Center.

I describe the new material across Snowflake courses, including a video overview and a brief practice test, and highlight the SnowPro Core certification as the prerequisite for all advanced certifications.

Navigate SnowPro certifications, from the core fundamentals to five advanced tracks (Architect, Data Engineer, Data Analyst, Data Scientist, Administrator), including online Pearson testing and renewal details.

Learn the SnowPro Core Certification as Snowflake's foundational credential, covering architecture, security, data loading, transformations, and time travel, with 100 questions in 2 hours and automatic renewals after advanced certs.

Explore Snowflake’s compute and storage separation and data loading methods—data loading wizard, Snowpipe REST API, and bulk COPY INTO from internal or external stages—and identify blocking statements (update, delete, merge).

Master the Streamlit for Snowflake Masterclass hands-on by building Streamlit and native apps, prototyping with Python and SQL, deploying to the Streamlit Cloud, and sharing results.