Analytics Workspace Setup

This project provides a standard data analytics workspace setup for a B2B sales organization. It establishes a consistent directory structure, a Python virtual environment, and installs a typical data analytics stack to analyze CRM updates, email response history, and deal-stage transitions.

Setup

Follow these steps to set up your local development environment:

1. Clone the repository:

   git clone https://github.com/YOUR-USERNAME/analytics-workspace-setup.git
   cd analytics-workspace-setup

2. Create the virtual environment:

   • macOS/Linux:

     python3 -m venv venv

   • Windows:

     python -m venv venv

3. Activate the virtual environment:

   • macOS/Linux:

     source venv/bin/activate

   • Windows:

     venv\Scripts\activate

4. Install dependencies:

   pip install -r requirements.txt

Project Structure

• data/raw/: Contains raw, unaltered data files.
• data/processed/: Contains cleaned and processed data files ready for analysis.
• notebooks/: Contains Jupyter notebooks for exploratory data analysis and experimentation.
• scripts/: Contains Python scripts for data processing and pipeline tasks.
• output/: Contains output files like generated reports, figures, and exported models.

Notes

• This project requires environment variables for configuration (e.g., database credentials, API keys).
• Please copy the .env.example file to a new file named .env and fill in your own specific values.
• Do not commit your .env file to version control. It is already ignored by .gitignore.