# Task: Create Data Analysis Plan

## Description
Create a comprehensive data analysis plan for extracting insights, developing machine learning models, and implementing data pipelines to support project objectives.

## Input Required
- Business requirements or problem statement
- Available data sources and descriptions
- Expected outcomes or success criteria
- Technical constraints or limitations

## Steps

1. **Problem Definition**
   - Clearly articulate the business problem or opportunity
   - Define specific questions to be answered through analysis
   - Establish success metrics and evaluation criteria
   - Identify stakeholders and their requirements

2. **Data Assessment**
   - Inventory available data sources
   - Assess data quality, completeness, and accessibility
   - Identify data gaps and acquisition needs
   - Evaluate data privacy and compliance requirements
   - Define data sampling strategy if applicable

3. **Exploratory Analysis Planning**
   - Define key variables to explore
   - Plan initial data profiling and visualization
   - Identify potential relationships to investigate
   - Design statistical tests to validate hypotheses
   - Plan for outlier detection and handling

4. **Feature Engineering Strategy**
   - Identify potential features to create
   - Plan transformations and encoding methods
   - Define feature selection approach
   - Document dimensionality reduction techniques if needed
   - Plan feature validation methods

5. **Model Development Strategy**
   - Select candidate algorithms based on problem type
   - Define training and validation approach
   - Plan hyperparameter tuning methodology
   - Establish model evaluation metrics
   - Design model interpretability approach

6. **Data Pipeline Architecture**
   - Design data ingestion processes
   - Plan data transformation and storage
   - Define model training pipeline
   - Design inference pipeline for production
   - Plan for monitoring and retraining

7. **Implementation Roadmap**
   - Create phased implementation plan
   - Establish milestones and deliverables
   - Identify required resources and tools
   - Develop timeline aligned with project goals
   - Plan for knowledge transfer and documentation

8. **Review and Validation**
   - Validate plan against business objectives
   - Ensure technical feasibility
   - Confirm alignment with project timeline
   - Verify ethical considerations are addressed

## Output
A comprehensive data analysis plan that includes:
- Problem definition and success criteria
- Data assessment and preparation strategy
- Exploratory analysis approach
- Feature engineering plan
- Model development methodology
- Data pipeline architecture
- Implementation roadmap and timeline

## Validation Criteria
- Plan addresses the business problem completely
- Data sources and quality issues are thoroughly assessed
- Modeling approach is appropriate for the problem type
- Technical implementation is feasible within constraints
- Ethical considerations are properly addressed
- Plan can be executed within project timeline