Data Analysis Use-case Deepdive
Lightning-fast data cleaning and preparation powered by AI
Clean, prepare, and join messy datasets into analysis-ready tables using an agent-driven workflow that finds issues, proposes fixes, and validates results step by step with full transparency and auditability.
Use CasesOutputs we will build
Cleaned source tables with data quality issues identified and resolved.
A validated, analysis-ready master table created by joining your datasets.
A repeatable cleaning pipeline you can rerun on future raw extracts (same logic, consistent results).
Objectives
- Ingest raw files and automatically detect schema, types, and relationships.
- Profile data health using distributions, null patterns, duplicates, and unique value counts.
- Clean datasets via the /clean shortcut with agent-proposed, user-approved changes.
- Join tables, compute derived metrics, and validate outputs and calculations.
- Produce analysis-ready datasets without manual SQL or spreadsheet iteration.
- Create a transparent, validated workflow from raw inputs to production-grade tables.