Agentic AI for Data Analysis: Automating Business Intelligence

The BI Bottleneck

Business intelligence teams spend 70% of their time on data preparation, leaving only 30% for analysis. Agentic AI flips this by autonomously handling data collection, cleaning, and visualization generation.

Natural Language to SQL

import anthropic
client = anthropic.Anthropic()

def nl_to_sql(question: str, schema: str) -> str:
    response = client.messages.create(
        model='claude-sonnet-4-6',
        max_tokens=1024,
        system=f'Convert business questions to SQL. Schema: {schema}',
        messages=[{'role': 'user', 'content': question}]
    )
    return response.content[0].text

Key Capabilities

• Automated report generation without human intervention
• Anomaly detection with real-time KPI alerts
• Conversational drill-down analysis
• Cross-dataset correlation across multiple sources

Implement authorization checks before query execution. Provide complete schema documentation to maximize SQL accuracy.