AGENTIC AI · DATA · ANALYTICS·2025

Agentic Data Analyst

An agentic data analysis system that investigates datasets through schema discovery, SQL generation, execution, validation, anomaly investigation, and structured analysis.

AGENTIC DATA PIPELINE
SCHEMA DISCOVERY ACTIVE
DATABASE→SCHEMA DISCOVERY→QUERY PLAN
-- Generated Query with Sandboxed Execution:
SELECT cohort, AVG(retention_rate)
FROM telemetry_aggregates
GROUP BY 1 HAVING COUNT(*) > 50;
VALIDATION STATUSSQL Syntax & Safety Checked
ANALYSIS OUTPUTStructured Anomaly Report
EXECUTION: ISOLATED READ-ONLY SANDBOXSYNTHESIS COMPLETE
TECHNOLOGIES
PythonSQLFastAPIPostgreSQLPandasPydanticData Visualization
SYSTEM NATURE

Open-source engineering system and architectural prototype. No fabricated client metrics.

01 / THE PROBLEM

Traditional text-to-SQL solutions produce syntactically plausible queries that hallucinate table relationships, fail on edge cases, or miss deeper statistical anomalies hidden within business datasets.

02 / APPROACH & WHY I BUILT IT

Designed to turn high-level analytical questions into deep exploratory workflows by chaining schema inspection, query planning, sandboxed execution, self-correction, and statistical synthesis.

Combines a schema discovery engine, an LLM query planner, a sandboxed SQL execution environment, a results validator, and an analytical synthesis pipeline. The system operates iteratively: if a query fails or produces empty sets, the agent analyzes the dialect error or schema mismatch and self-heals.

03 / HOW THE SYSTEM WORKS

  1. 01.Extracts and indexes schema definitions, foreign keys, and statistical column distributions.
  2. 02.Translates analytical intent into a staged query plan before generating SQL code.
  3. 03.Executes queries in an isolated, read-only database transaction sandbox.
  4. 04.Validates output data against statistical sanity checks and sanity bounds.
  5. 05.Generates a comprehensive analysis report with key drivers, cohort comparisons, and dynamic visualization configurations.

04 / KEY ENGINEERING DECISIONS

  • ✦Read-only sandboxing with transaction rollback guarantees zero risk of state-modifying SQL execution.
  • ✦Pre-execution validation passes through SQL dialect parsers to catch syntax errors before database roundtrips.
  • ✦Structured anomaly detection routines to highlight outlier values rather than merely regurgitating raw rows.

05 / RELIABILITY & FAILURE BOUNDARIES

Implements query execution time limits (statement_timeout), maximum row constraints, and strict schema guardrails to prevent accidental denial-of-service on analytical stores.