DAPM Framework

Data Analytics Project Methodology

Business First. Evidence Always.

Property	Value
Current Version	v0.2.1
Release Status	Experimental
Framework Type	Business-First Data Analytics Methodology
License	CC BY-NC-SA 4.0

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📝 Overview

The Data Analytics Project Methodology (DAPM) is an open-source framework that provides a structured, repeatable, and business-first approach to executing end-to-end data analytics projects.

Instead of beginning with datasets, dashboards, or programming languages, DAPM begins with the business problem.

The methodology guides analysts from understanding the business through data preparation, analysis, insights, and evidence-based recommendations.

DAPM is technology-independent and can be applied using spreadsheets, SQL, Python, R, Power BI, Tableau, or any analytical platform.

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💡 Why DAPM?

Many analytics projects begin with data.

DAPM begins with the business.

This simple shift helps ensure that every analysis answers a business question and every recommendation is supported by evidence.

The framework promotes disciplined analytical thinking rather than tool-specific workflows.

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📌 Supported Project Types

DAPM is designed to support different types of analytics projects.

Project Type	Supported
Client Consulting Projects	✅
Internal Business Projects	✅
Portfolio Projects	✅
Academic Case Studies	✅
Kaggle Projects	✅
Self-learning Projects	✅

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📝 Documentation

The framework documentation is organized into focused documents.

Document	Description
ARCHITECTURE	Official DAPM workflow and phase responsibilities.
PHILOSOPHY	The ideas and mindset behind the methodology.
PRINCIPLES	Core principles followed by every DAPM project.
TERMINOLOGY	Standard terminology used throughout the framework.
ROADMAP	Planned improvements and future releases.
VERSIONING	Versioning strategy for DAPM releases.

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🗂️ Template Library

DAPM includes a standardized documentation library for analytics projects.

Templates are currently under validation through practical implementations.

Template	Purpose
Project Brief	Defines the business problem and project scope.
Project Summary	Summarizes the completed engagement.
Business Understanding	Documents business operations and context.
Stakeholder Analysis	Identifies stakeholders and their information needs.
Business Requirements	Defines business questions, KPIs, and reporting needs.
Data Discovery	Documents available datasets and data sources.
Data Profiling	Records the characteristics of the raw dataset.
Validation Report	Documents business validation results.
EDA Report	Records exploratory analysis and observations.
Business Insights	Converts findings into business understanding.
Recommendations	Provides evidence-based business actions.
Executive Summary	Presents findings for decision makers.

🗂️ See the complete template library in templates/.

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💻 Validation Projects

DAPM follows an evidence-driven development approach.

Every architectural decision, document, and template is validated through practical analytics projects before becoming part of a stable release.

Current validation projects include:

• WAVE Warehouse Operations & Inventory Analytics
• LOGIX Distribution Center & Logistics Analytics

Future validation projects will expand into additional business domains.

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📁 Repository Structure

DAPM
├── assets
│   └── images   
├── CHANGELOG.md
├── CODE_OF_CONDUCT.md
├── CONTRIBUTING.md
├── docs
│   ├── ARCHITECTURE.md
│   ├── PHILOSOPHY.md
│   ├── PRINCIPLES.md
│   ├── ROADMAP.md
│   ├── TERMINOLOGY.md
│   └── VERSIONING.md
├── GLOSSARY.md
├── LICENSE
├── METHODOLOGY_COMPARISON.md
├── METHODOLOGY.md
├── README.md
├── SECURITY.md
└── templates
    ├── 00_README_TEMPLATE.md
    ├── 01_PROJECT_BRIEF.md
    ├── 02_BUSINESS_UNDERSTANDING.md
    ├── 03_STAKEHOLDER_ANALYSIS.md
    ├── 04_BUSINESS_REQUIREMENTS.md
    ├── 05_DATA_DISCOVERY.md
    ├── 06_DATA_PROFILING.md
    ├── 07_DATA_CLEANING.md
    ├── 08_DATA_VALIDATION.md
    ├── 09_EDA_REPORT.md
    ├── 10_BUSINESS_INSIGHTS.md
    ├── 11_RECOMMENDATIONS.md
    ├── 12_EXECUTIVE_SUMMARY.md
    ├── ANALYTICAL_THINKING.md
    ├── OBSERVATIONS.md
    ├── PHASE_CHECKLIST.md
    ├── PROJECT_SUMMARY.md
    └── README.md

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🚀 Getting Started

1. Read the Architecture document.
2. Understand the Philosophy and Principles.
3. Review the project templates.
4. Follow the DAPM workflow throughout your analytics project.
5. Validate findings before making business recommendations.

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📝 Version Status

DAPM is currently under active development.

The methodology evolves through practical implementation rather than theoretical assumptions.

Every significant change is validated before being included in a stable release.

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🎯 Roadmap

Future releases will focus on:

• Additional validation projects
• Improved documentation
• Domain-specific blueprints
• Community contributions
• Methodology refinement based on practical evidence

See Roadmap for details.

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👥 Contributing

DAPM is an open and evolving methodology.

Suggestions, discussions, validation findings, and improvements are welcome.

Please open an Issue or submit a Pull Request if you would like to contribute.

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📜 License

DAPM Framework © 2026 Subir Sutradhar

Licensed under CC BY-NC-SA 4.0.

See the LICENSE file for complete licensing information.

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Business First. Evidence Always.