• 🔴 Do your ML projects stall because data is dirty or incomplete?
    We prepare datasets ready for training.
  • 🔴 Do teams rebuild the same extraction scripts?
    We centralize collection and deliver shared datasets.
  • 🔴 Do you want to open source part of the data but it's a mess?
    We produce a clean public version.
🔴 The model isn't weak. The dataset is. Agree?
We fix the dataset side.
🔴 Do your data scientists spend 80% of time cleaning instead of modeling?
We take that 80% away.
💯 Practice Areas
ADG Data Preparation & Open Sourced Enhancement collects, cleans, deduplicates and enriches data from multiple sources, documents it and packages it for ML and analytics teams.

You get reproducible datasets and faster model delivery.

🔸 Ready to use datasets for ML/BI.
🔸 Faster model delivery (data part already done).
🔸 Single source of truth instead of 5 ad hoc exports.
🔸 Ability to publish/open source part of data.
🔸 Documentation for onboarding new team members.
🔸 Repeatable data factory.
How It Works
Inventory & keys
Enumerate DBs/APIs/files, define join keys and ID contracts so downstream joins stop breaking.
Ingest & stage
Build repeatable pulls with lineage and schema checks. Stage raw and cleaned layers for reproducibility.
Clean & normalize
Dedup, type fix, reconcile codes. Small, audited transforms that are easy to diff when something regresses.
Enrich & features
Add open data, compute features that lift models or BI. Keep feature logic as code with tests.
Pack & publish
Deliver Parquet/CSV plus schemas, sample queries and a quick start. No vendor lock-in, just files and contracts.
Validate & handoff
Business spot checks, data QA, and handover of refresh cadence and ownership.
Refresh (optional)
Scheduled deltas, quality gates, versioned releases so analysts and models don’t break when inputs change.
Documentation & Reporting (optional)
We produce lean, engineer-first artifacts that can scale to audit grade if needed - diagrams, IaC refs, runbooks, SLO dashboards, and change logs. Evidence packs are versioned and reproducible: links point to live systems or CI exports, not slides. Scope is tailored per client - from a 1-page ops sheet to a full compliance bundle with test replays and data lineage. If you prefer, we keep it minimal and focus on code and metrics only.
What you pay for
  • 🟢 One-off dataset build
    Source discovery, cleaning, dedup, normalization, docs.
  • 🟢 Monthly refresh
    Scheduled extractions, delta processing, QA checks.
  • 🟢 Data factory retainer
    Ongoing enrichment, feature engineering, versioning.

General transparency note

Pricing reflects two components where applicable:
✅ Expert work
Architecture, implementation, monitoring, reporting.
✅ Resources
Compute, storage, network and third-party tooling used to meet your SLAs
Legal reviews, open-data publication and sensitive PII handling are quoted case-by-case.

We keep these components itemized so you see exactly what delivers the outcome.