Purpose:

Transform raw data into actionable insights by leveraging AI for data processing while utilizing human expertise for context and strategic recommendations.

Workflow Steps:

1. Requirements Definition (Human)
   • Clarify analysis objectives and key questions
   • Identify relevant data sources and metrics
   • Establish report format and audience
2. Data Preparation (AI + Human)
   • Human Task: Access and connect data sources
   • AI Task: Clean data, identify anomalies, and standardize formats
   • Human Task: Verify data quality and resolve access issues
   • AI Task: Create initial data relationships and models
3. Analysis Execution (AI)
   • Run statistical analyses based on requirements
   • Generate visualizations of key trends and patterns
   • Identify correlations and potential insights
   • Prepare preliminary findings
4. Insight Development (Human + AI)
   • Human Task: Review AI-generated findings
   • AI Task: Answer follow-up questions and drill deeper
   • Human Task: Apply business context to findings
   • AI Task: Generate additional visualizations as needed
5. Report Creation & Delivery (AI + Human)
   • AI Task: Draft report with key findings and visualizations
   • Human Task: Add strategic recommendations and context
   • AI Task: Format report for presentation
   • Human Task: Present findings to stakeholders

Handoff Protocol:

• Analysis notebooks with documented code and queries
• Shared dashboards for collaborative review
• Clear documentation of data sources and methodologies

Quality Control:

• Data validation checks at preparation stage
• Peer review of statistical methods
• Stakeholder feedback on insight relevance