bidoc 1.0.0

Business Intelligence documentation tool for Power BI and Tableau

BI Documentation Tool

A powerful command-line tool for automatically generating comprehensive documentation from Business Intelligence files. Supports Power BI (.pbix) and Tableau (.twb/.twbx) workbooks, extracting detailed metadata to produce professional Markdown and JSON documentation.

🎉 Version 1.0.0 - Production Ready! Complete with enterprise integration hooks for tools like Ataccama, Confluence, SharePoint, and more.

🚀 Key Features

• Multi-Format Support: Parse Power BI (.pbix) and Tableau (.twb/.twbx) files
• Rich Metadata Extraction: Complete extraction of tables, fields, measures, calculations, data sources, and relationships
• Dual Output Formats: Generate both human-readable Markdown and machine-readable JSON
• Enterprise Integration: Built-in hooks for Ataccama, Confluence, SharePoint, Microsoft Purview, and more
• Docker Ready: Containerized for easy CI/CD integration
• Batch Processing: Process multiple files simultaneously
• Cross-Platform: Works on Windows, macOS, and Linux
• Robust Testing: 48+ comprehensive tests ensuring reliability
• DAX Formatting: Professional formatting of DAX expressions in output

📋 Quick Start

Prerequisites

• Python 3.8 or higher
• pip package manager

Installation

Option 1: Local Installation

# Clone the repository
git clone <repository-url>
cd bi-doc

# Create virtual environment (recommended)
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Install the package in development mode
pip install -e .

Option 2: Docker (Recommended for CI/CD)

# Build the Docker image
docker build -t bidoc-tool .

# Verify installation
docker run bidoc-tool --help

🔗 Enterprise Integration

The BI Documentation Tool provides comprehensive integration capabilities for enterprise data management platforms:

• Data Catalogs: Ataccama DGC, Microsoft Purview, Apache Atlas, DataHub
• Documentation Platforms: Confluence, SharePoint, GitBook, Notion
• CI/CD Pipelines: GitHub Actions, Azure DevOps, Jenkins
• Custom APIs: RESTful endpoints for internal systems

See INTEGRATION_HOOKS.md for detailed implementation examples and best practices.

Basic Usage

# Parse a single Power BI file
python -m bidoc -i report.pbix -o docs/ -f all

# Parse a Tableau workbook with verbose output
python -m bidoc -i dashboard.twbx -o docs/ -f markdown --verbose

# Batch processing multiple files
python -m bidoc -i *.pbix -i *.twbx -o docs/ -f all

# Generate AI-enhanced summaries (when configured)
python -m bidoc -i report.pbix -o docs/ --with-summary

Docker Usage

# Build the Docker image
docker build -t bidoc-tool .

# Run with mounted volumes
docker run -v $(pwd):/data bidoc-tool --input /data/report.pbix --output /data/docs

📖 Documentation

• User Guide - Comprehensive usage guide with examples
• Integration Hooks - Enterprise integration patterns and examples
• Roadmap - Development roadmap and planned features
• Contributing - How to contribute to the project
• Changelog - Version history and changes

🔍 What Gets Extracted

Power BI (.pbix)

• Data Model: Tables, columns, data types, relationships
• DAX Measures: All measures with their formulas
• Calculated Columns: Custom calculations and their DAX expressions
• Data Sources: Connection details and source information
• Report Layout: Pages, visuals, and field mappings
• Power Query: M code and transformation steps

Tableau (.twb/.twbx)

• Data Sources: Connection details and database information
• Fields: Dimensions, measures, calculated fields with formulas
• Worksheets: Individual sheet layouts and field usage
• Dashboards: Dashboard structure and contained worksheets
• Parameters: User-defined parameters and default values

📄 Output Examples

Markdown Output

# Documentation for Sales Dashboard

## Data Sources
- **SQL Server**: server01.company.com/SalesDB
- **Excel File**: Q4_Targets.xlsx

## Tables and Fields
### Sales
| Field Name | Type | Description |
|------------|------|-------------|
| SalesAmount | Decimal | Total sales value |
| CustomerID | Integer | Customer identifier |
| TotalSalesYTD* | Decimal | Calculated: `SUM(Sales[SalesAmount])` |

## Visualizations
### Page: Overview
- **Bar Chart**: Sales by Region
  - Fields: [Geography.Region], [Sales.TotalSalesYTD]
- **Card**: Total Revenue
  - Field: [Sales.TotalSalesYTD]

JSON Output

{
  "file": "sales_dashboard.pbix",
  "type": "Power BI",
  "data_sources": [
    {
      "name": "SalesDB",
      "connection": "sqlserver://server01.company.com/SalesDB",
      "tables": [
        {
          "name": "Sales",
          "columns": [
            {"name": "SalesAmount", "data_type": "Decimal"},
            {"name": "CustomerID", "data_type": "Integer"}
          ],
          "measures": [
            {"name": "TotalSalesYTD", "expression": "SUM(Sales[SalesAmount])"}
          ]
        }
      ]
    }
  ]
}

🏗️ Architecture

The tool follows a modular architecture with clear separation of concerns:

bidoc/
├── cli.py              # Command-line interface
├── pbix_parser.py      # Power BI parsing logic
├── tableau_parser.py   # Tableau parsing logic
├── markdown_generator.py  # Markdown output formatting
├── json_generator.py   # JSON output formatting
├── ai_summary.py       # AI integration hooks
└── utils.py           # Common utilities

🚀 Current Status & Roadmap

✅ Completed Features

• Multi-format Support: Robust parsing of Power BI (.pbix) and Tableau (.twb/.twbx) files
• Rich Metadata Extraction: Complete extraction of datasets, fields, measures, calculations, and visuals
• Dual Output Formats: High-quality Markdown (markdownlint compliant) and structured JSON
• Production Ready: Robust CLI, Docker support, comprehensive error handling
• Batch Processing: Efficient processing of multiple files with detailed logging
• Modular Architecture: Extensible design ready for future enhancements

🔄 Next Priorities

For detailed roadmap and quality-of-life improvements, see QOL_SUGGESTIONS.md:

• Enhanced User Experience: Progress indicators, better error messages, interactive mode
• Performance Optimizations: Parallel processing, incremental updates, caching
• Output Quality: Enhanced Markdown with TOC, collapsible sections, syntax highlighting
• Enterprise Integration: Git hooks, Confluence export, SharePoint integration
• Advanced Analytics: Usage patterns, similarity detection, AI-powered insights

🔧 Dependencies

• pbixray: Power BI file parsing (>=0.3.3)
• tableaudocumentapi: Tableau workbook parsing (>=0.11)
• click: CLI framework (>=8.0.0)
• jinja2: Template rendering (>=3.1.0)
• pandas: Data processing (>=1.5.0)
• lxml: XML processing (>=4.9.0)
• colorama: Cross-platform colored output (>=0.4.0)

🙏 Acknowledgments

We are grateful to the open-source community and the following projects that make this tool possible:

• PBIXRay by Arjen van Stam - Essential Power BI file parsing capabilities
• Tableau Document API by Tableau Software - Comprehensive Tableau workbook analysis
• Microsoft - Power BI sample files for testing and demonstration
• Python Community - The amazing ecosystem of libraries (pandas, click, jinja2, etc.)

For complete attribution and licensing information, see THIRD_PARTY_LICENSES.md.

🤝 Contributing

We welcome contributions! Please see our contributing guidelines:

1. Fork the repository
2. Create a feature branch: git checkout -b feature/your-feature
3. Make your changes and add tests
4. Ensure all tests pass: python -m pytest tests/ -v
5. Submit a pull request

Development Setup

# Clone and setup development environment
git clone <repository-url>
cd bi-doc
python -m venv .venv
source .venv/bin/activate  # or .venv\Scripts\activate on Windows
pip install -r requirements.txt
pip install -e .

# Run tests
python -m pytest tests/ -v

# Run with coverage
pip install pytest-cov
python -m pytest --cov=bidoc tests/

📄 License

This project is licensed under the Business Source License 1.1 (BSL) - see the LICENSE file for details.

🆘 Support

• Documentation: See USER_GUIDE.md for detailed usage instructions
• Integration Guide: See INTEGRATION_HOOKS.md for enterprise integration patterns
• Issues: Report bugs and feature requests on GitHub
• Discussions: Join community discussions for questions and ideas

📊 Status

• ✅ Production Ready: All core features implemented and tested
• ✅ Docker Support: Containerized for easy deployment
• ✅ CI/CD Ready: Automated testing and deployment pipelines
• ✅ Enterprise Integration: Hooks for major data platforms
• 🔄 Active Development: Regular updates and new features

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Made with ❤️ for the BI community