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Data Engineering

Turn raw operational data into analytics-ready, governed datasets

DataForge ingests raw source files and operational data in multiple formats, refines them through a structured bronze → silver → gold (medallion) pipeline, and produces clean, modeled, analytics-ready datasets — with full lineage and documentation for every transformation.

DataForge AI Session Workspace showing business goal setup, file ingestion, and the bronze-silver-gold pipeline
Designed for

Data engineering teams, quality and operations analysts, manufacturing data teams, BI and reporting teams, governance and compliance teams, and digital transformation teams

How it works

01

Define Business Context

Set up your business goal, problem, scope, and KPIs with the AI Context Builder.

02

Upload Raw Data

Bring in your uncleaned CSV, TSV, Excel, or JSON files for automatic ingestion and profiling.

03

Clean & Profile

The AI automatically detects column types, identifies errors, and applies deterministic or LLM cleaning rules.

04

Auto-Join Files

The system discovers relationships across multiple uploaded datasets and recommends safe joins.

05

Generate Gold Data & Insights

Build a unified Gold dataset, auto-generate visual dashboards, and create AI-narrated insights.

06

Build a Knowledge Graph

Generate an ontology, knowledge graph, SPARQL queries, and business rules from your Gold dataset.

Features

Automatic column profiling, data type detection, and deterministic or LLM-assisted cleaning — date normalization, null filling, deduplication, and unit conversion in one click.

Multi-file intelligence that auto-detects relationships across uploaded datasets, recommends safe joins, and builds one unified Gold dataset.

Auto-generated YAML data contracts with typed columns, quality scoring, and DuckDB-compatible SQL validation rules.

Built-in data governance — automatic PII scanning and schema drift detection flag risk on every upload.

Visual dashboard generation with auto-built KPIs and charts, plus LLM-narrated findings, risks, and recommended actions.

A semantic Knowledge Graph layer — generate an ontology, build triples from your Gold dataset, query with SPARQL, and apply business rules.

Works fully without API keys; optionally connect OpenAI, Anthropic, or Gemini for dynamic SQL generation and AI insight narratives.

Key benefits

What your team can do faster

Convert raw files into governed, analytics-ready Gold datasets with full lineage

Auto-generate dashboards, KPIs, quality scorecards, and data contracts

Built-in PII scanning, schema drift detection, and semantic knowledge graphs

Product descriptions, screenshots, workflows, and demonstrations are provided for evaluation purposes only. No rights are granted except as expressly agreed in writing by QDES.

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