Lakewright solutions / brief
Load mainframe fixed-width files into Apache Iceberg
Fixed-width mainframe extracts — no headers, no delimiters — become typed Iceberg tables. Lakewright infers the column layout from the data itself, and the layout is recorded in a reviewable plan before anything loads.
How can columns be inferred without a copybook?
Character-class transitions (digit runs, space gutters, date shapes) that hold across sampled lines mark column boundaries. Every inferred boundary is visible in the plan YAML — a human confirms the layout before the first row lands. If you have the copybook, you edit the plan to match; the plan is the contract either way.
The steps
lakewright scan /transfer/legacy-extracts lakewright plan /transfer/legacy-extracts --out plans # review layout lakewright approve plans/policy_master.plan.yaml lakewright load plans/policy_master.plan.yaml --rest $CATALOG
FAQ
The question that matters
"Which policy cohorts lapsed within ninety days of the 2025 rate change, and what premium did we lose?"
The answer arrives grouped by cohort with premium at risk attached — from a file that has no headers, no delimiters and no copybook that anyone could still find.
What makes the answer trustworthy is upstream of the query: the inferred column layout was shown as a plain YAML plan and approved by someone who knows the policy system before a single row loaded. So when the assistant reports that one cohort lapsed at several times the rate of the others, the column it grouped by means what your team confirmed it means, rather than what a parser guessed.
The follow-up question — whether those lapses concentrate in a particular issue year or agent — is the same shape of query, and takes seconds rather than another extract request to the mainframe team.
Want this run against your data?
We start with a read-only scan and an inventory report — no installation on your systems, nothing leaves your environment. Most engagements produce findings the team didn't know about in the first afternoon.