Arkham Analytics is a data consultancy built on one principle: data must be trustworthy before it can be useful. We enforce governance, build repeatable pipelines, and make sure every record in your system can prove where it came from and what happened to it.
Most teams reach for answers before their data is ready to give them. We work the other way. We establish governance frameworks, data contracts, and quality standards before anything else — because a fast answer built on bad data is worse than no answer at all. Every dataset we touch gets a documented owner, a defined schema, and a clear chain of custody.
We build pipelines with audit columns on every table — created_at, updated_at, source_system, record_hash. We implement SCD Type 2 where history matters. We track lineage from raw ingestion to final output. If something breaks, you know exactly when, where, and why — because we designed the system to tell you.
Every engagement is held to the same standard. These aren't best practices — they're the floor, not the ceiling.
Every dataset gets an owner, a schema contract, and a freshness SLA. We define governance policies before we write a single pipeline — access controls, retention rules, classification tiers. Your data catalogue is not optional documentation; it's the foundation everything else is built on.
We never overwrite records — we version them. SCD Type 2 on every dimension that changes. Audit columns on every table: valid_from, valid_to, is_current, created_by. If a number changed, you can see exactly when, what it was before, and what triggered the change.
If a data fix cannot be encoded into a repeatable, testable pipeline step, it doesn't happen. No one-off scripts. No undocumented transformations. Every cleaning rule is version-controlled, peer-reviewed, and idempotent — run it once or a thousand times, the result is identical.
We instrument pipelines with data quality checks at every layer — completeness, uniqueness, referential integrity, distribution drift. Alerts fire before downstream teams notice. Whether you're running analytics or training an LLM, the data your models see is the data we've certified — not approximated.
Drop any raw dataset. Our engine will profile it — completeness, uniqueness, validity, consistency — and surface a data quality scorecard showing exactly what's clean, what's broken, and what governance rules it violates. The diagnosis is always free.
Sign up to receive the full quality report, a remediation plan, audit-ready documentation, and your cleaned dataset with lineage tracking applied.
Join data teams who've stopped guessing and started governing. Every pipeline we deliver is documented, tested, auditable, and built to the same standard — whether you're running dashboards or training models.