Describe the output you need, upload a sample result, paste a field list, or connect your existing data. Datalena maps the requirements, combines the sources, identifies what is missing, and builds a governed workflow your team can review and repeat.
Build this monthly performance package from the files we receive from each location.
I found 17 of the 19 required fields. Region can be derived from the location reference. Two calculation rules still need your input.
The path between: evidence and requirements meet, a governed plan is approved, deliverables ship.
One governed workflow
A dashboard is one output. The same governed dataset can power files, feeds, portals, and APIs.
Describe the output you need, show Datalena a sample, connect what you already have, or do both. The same governed design process connects the two sides.
Upload the report, workbook, or feed you need to produce — or just describe it.
Datalena decomposes it into required fields, calculations, and delivery rules, then hunts for the evidence.
Connect the files and exports you already have, messy layouts and all.
Datalena maps what each source can prove and shows which outputs are already within reach.
Bring the target and the evidence together.
Datalena works backward from the result and forward from the sources until they meet in one governed plan.
Whichever door you pick, the same governed path meets in the middle.
The hard part is not storing data or drawing a dashboard. It is turning changing source evidence into a repeatable, governed result without rebuilding the logic every cycle.
Workbooks, exports, APIs, reference data, prior-period files, and manual corrections keep their source identity.
Datalena binds requirements to evidence, proposes transformations, exposes gaps, and keeps the decisions reviewable.
The output contract works backward into required fields, calculations, quality rules, access scopes, and delivery behavior.
Datalena turns plain-language intent and source evidence into a versioned specification, then executes the approved workflow deterministically.
Define — the same composition, one layer further.
Tell Lena the result you need — or hand it a sample. The target becomes an explicit output contract.
Point Datalena at the evidence you already have. Every source stays identifiable by type and purpose.
Requirements and evidence meet: direct matches, derivations, transformations — and the gaps, kept visible.
Your team inspects readiness, open questions, and held rows. Nothing proceeds on AI say-so alone.
After your approval, the workflow runs deterministically and produces every governed output — every cycle.
Each source is standardized into a reliable structure, then combined, reconciled, and validated before anything ships. Source identity and lineage remain intact along the way.
Use conversation to design and revise the workflow. Datalena preserves the operational contract as an explicit, versioned specification with validation, lineage, and approval history.
Once the workflow is approved, recurring runs execute against that active spec. Clean cycles can proceed according to policy; Datalena pauses when drift, validation failures, or a material exception needs a decision.
What arrives, what Datalena assembles, and what gets published can change. The governed path stays consistent.
From Insights
Data Operations
A field guide to replacing monthly spreadsheet heroics with a repeatable intake, standardization, validation, review, and delivery process that can handle known variation safely.
Read insight →Data Assembly
A practical framework for choosing source-first, outcome-first, or hybrid workflow design while keeping the final production execution forward, explicit, and deterministic.
Read insight →Governed Data
A practical definition of a governed dataset and the operational properties that make it safe to reuse across recurring dashboards, files, feeds, and other client deliverables.
Read insight →Start with a sample output, the sources you already receive, or both. Datalena will build the reviewable, repeatable workflow between them.