Streamlit output1
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Imagine a sales team at a fast-growing software company. They rely on a robust understanding of sales performance across different regions and product lines to make informed decisions and optimize sales strategies. The primary objective of this use case is to develop an interactive sales data dashboard that allows business users to monitor and analyze sales performance in real-time using Streamlit. The dashboard will provide a comprehensive overview of sales transactions, offer insights into sales performance by region and product, and enable users to filter and explore data interactively.


  1. Snowflake: Cloud data platform for storing and processing sales data.
  2. Snowpark: Snowflake’s DataFrame-based API for efficient data manipulation.
  3. Streamlit: Open-source app framework for building interactive web applications.

Key Features:

  1. Data Overview: Display all completed sales transactions.
  2. Sales Summary by Region: Summarize total sales amounts for each region.
  3. Sales Summary by Product: Summarize total sales amounts for each product.
  4. Interactive Charts: Visualize sales data using bar charts.
  5. Data Filtering: Allow users to filter and explore sales data based on regions.

Implementation Steps:

  • Create a Streamlit app with a title and subheader.
  • Display the sales data overview using Streamlit’s write method.
  • Generate summaries of total sales by region and product.
  • Create interactive charts using Altair and embed them in the Streamlit app.
  • Add functionality to filter sales data by region and display the filtered results.


Sales Streamlit


Streamlit output
Streamlit output1
Streamlit output2

This use case demonstrates how Snowflake, Snowpark, and Streamlit can be leveraged together to create an effective tool for monitoring and analyzing sales data, ultimately driving better business outcomes.

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