Over 90% of mid-to-large organisations now run a cloud data warehouse — and the lakehouse pattern, built on the open Apache Iceberg table format, is the 2026 default starting point for a new one. We move you there without losing a row.
Gartner classifies the lakehouse shift as transformational. Apache Iceberg is the open table format underneath it — the reason a lakehouse doesn't just recreate warehouse lock-in with extra steps.
Apache Iceberg stores data once, in open Parquet files, readable by Spark, Databricks, Fabric, or Snowflake — no re-export to switch engines.
ACID guarantees on every write, so concurrent pipelines and readers never see a half-written table.
Add, rename, or widen columns without rewriting history or breaking queries already running against the table.
Query any prior snapshot of a table — an audit trail for the data itself, not just the pipeline that produced it.
The methodology, not the destination platform, is what protects you. Every migration ships with a reconciliation report before production ever points at the new lakehouse.
Inventory every source table, its row volume, and who depends on it downstream.
Map the target Iceberg schema and decide what changes now versus what's preserved as-is.
Load into the lakehouse while the legacy warehouse keeps serving production — no forced cutover.
Row-count parity and value-level spot checks between source and target before anyone flips the switch.
If your source of truth today is scattered spreadsheets and manual exports, the target is the same governed lakehouse — we just start the reconciliation from a messier baseline.
Lineage, retention, and access controls all sit on top of the same warehouse foundation — score yourself against the checklist to see where you stand.
Tell us about your current warehouse or spreadsheets — we'll scope the migration and send a quote.
