guzmanwolfrank/snowflake

Connects to a Snowflake database named 'Transactions' and executes 10 SQL Queries.

A collection of Snowflake Apps and Tools.

Snowflake Data Analysis Project

This project is aimed at performing data analysis on transactions stored in a Snowflake database. It involves uploading transaction data from a CSV file into a Snowflake table, executing SQL queries to analyze the data, and displaying the results.

Features

• Data Upload: Upload transaction data from a CSV file into a Snowflake table.
• Data Analysis: Perform various data analysis tasks using SQL queries on the Snowflake database.
• Result Visualization: Display the results of the data analysis queries.

Prerequisites

Before running the project, ensure you have the following installed:

• Python 3.x
• snowflake-connector-python library
• pandas library

Project Files

• README.md: This file provides an overview of the project, including setup instructions, usage guidelines, and other relevant information.

• SnowflakeQueries.ipynb: This Jupyter Notebook contains a collection of SQL queries used for data analysis on transactions stored in a Snowflake database.

• Transactions.csv: This CSV file contains raw transaction data. It serves as the input for the Snowflake data analysis project.

• generator.ipynb: This Jupyter Notebook contains the Python code used to generate fake transaction data for testing and development purposes.

• transactions.db: This SQLite database file stores transaction data locally. It is used for testing and development purposes.

• snowflake_script.py: Main program. SQL queries used for data analysis on transactions stored in a Snowflake database.

Setup

1. Clone the repository:

   git clone https://github.com/your_username/snowflake-data-analysis.git
   cd snowflake-data-analysis

2. Install dependencies:

   pip install snowflake-connector-python pandas

3. Update Snowflake connection parameters:

   Open the snowflake_script.py file and replace the placeholders (<your_user>, <your_password>, <your_account>, etc.) with your actual Snowflake credentials.

Usage

1. Place your CSV file containing transaction data in the project directory.

2. Run the snowflake_script.py script to upload the CSV file to a Snowflake table, execute the predefined SQL queries, and print the results:

   python snowflake_script.py

Contributing

Contributions are welcome! Please feel free to submit a pull request or open an issue for any bugs, feature requests, or improvements.

License

This project is licensed under the MIT License - see the LICENSE file for details.