Data preparation workflows
Turn messy business files into clean, structured outputs.
Valiance Labs builds data preparation workflows for teams working with recurring spreadsheets, CSVs, exports, PDFs, and other business inputs. We clean, map, validate, and structure the data so it can be used for reporting, dashboards, imports, migrations, or analysis.
Messy file workflow
The file cleanup your team keeps repeating is the real starting point.
Recurring business files often need the same preparation before anyone can use the data: cleanup, mapping, consolidation, validation, exception review, and a controlled output.
- 01Receive messy business filesSpreadsheets, CSVs, exports, PDFs, reports, shared folders, and system downloads arrive from different people or tools.
- 02Clean, map, and consolidateSomeone standardizes headers, maps fields, combines files, normalizes names and dates, and keeps track of source issues.
- 03Validate and flag exceptionsMissing fields, duplicate rows, changed layouts, malformed values, and unusual records need to be caught before the output is used.
- 04Create the clean outputThe prepared data becomes a clean CSV, standardized table, dashboard-ready dataset, import file, migration file, or analysis-ready export.
Usable outputs
Clean structured data can feed more than a dashboard.
The deliverable is a prepared output your team can actually use: for reporting, dashboards, imports, migrations, internal systems, or analysis.
Clean CSV/XLSX or standardized table
A controlled output that replaces ad hoc spreadsheet cleanup and gives the team a consistent structure to use.
Import-ready or migration-ready data
Mapped fields, required values, deduplicated records, and validation notes before data enters another system.
Dashboard-ready or report-ready export
Prepared data that can feed Power BI, Tableau, Looker, Excel models, reporting packages, or recurring stakeholder outputs.
Validation report or exception list
A reviewable record of missing fields, changed layouts, duplicates, malformed values, and rows that need human judgment.
Existing stack
Built around existing tools where they are enough.
Excel, Power Query, OpenRefine, Tableau Prep, scripts, connector tools, BI tools, and data platforms can all be useful. Valiance Labs fits when the recurring preparation workflow needs custom structure around messy inputs, mapping, validation, exceptions, source history, and clean outputs.
Excel, Google Sheets, shared folders, spreadsheets, CSV exports, PDFs, and recurring business reports
Power Query, OpenRefine, Tableau Prep, scripts, connector tools, and controlled import/export templates
Power BI, Tableau, Looker, Excel models, databases, CRMs, and internal systems that need prepared data
Accounting, ERP, CRM, payroll, payment, operations, vendor, client, operator, and location systems
Data preparation
What the preparation workflow actually handles.
Data preparation is the center of the offer: clean and structure files, consolidate spreadsheets and exports, validate fields, flag exceptions, and produce clean outputs.
Clean & structure files
Standardize headers, clean text, normalize dates and categories, handle missing values, and structure inconsistent spreadsheets, CSVs, exports, and reports.
Consolidate spreadsheets and exports
Combine recurring files, merge source variations, map fields across layouts, preserve source information, and produce one structured output.
Validate fields and flag exceptions
Check required fields, duplicates, formats, missing files, changed headers, unusual values, and rows that need review.
Produce usable outputs
Create clean CSV/XLSX files, standardized tables, import-ready data, dashboard-ready datasets, report-ready exports, migration-ready files, and analysis-ready datasets.
Use Cases
Where clean structured data can go next.
Prepared data can support reporting, dashboards, imports, migrations, analysis, internal systems, and repeatable report outputs.
Project start
Start with the files and output you need.
You do not need clean data, a technical spec, or a chosen solution. A rough description of the current files, cleanup steps, and desired output is enough to start.
The spreadsheets, CSVs, exports, PDFs, or reports your team receives
A sample current file or redacted example
The cleanup, mapping, consolidation, or validation steps repeated today
The clean output you need: CSV, XLSX, table, import file, dashboard dataset, report export, or analysis dataset
The downstream use: reporting, dashboard, import, migration, internal system, or analysis
The fields, values, duplicates, layout changes, or exceptions that need review
Practical answers
What teams usually ask before starting.
If your workflow is still unclear, that is fine. Start with the files, the current cleanup steps, and the output your team needs.
Do we need to know the technical solution first?+
No. Start with the files, the current cleanup steps, and the output your team needs. The workflow determines whether existing tools, custom logic, or both make sense.
Is this replacing Excel, Power Query, Tableau Prep, or BI tools?+
Not by default. Those tools often remain useful. Valiance Labs fits when the recurring preparation workflow needs more structure around messy inputs, mapping, validation, exceptions, and clean outputs.
Can you work with the tools we already use?+
Usually, yes. The right approach may use existing spreadsheets, BI tools, import templates, connector tools, scripts, databases, or custom code depending on the workflow.
Do we need clean files before starting?+
No. Messy files, inconsistent exports, and review steps are often the reason to start. The first step is understanding what needs to be cleaned, mapped, validated, and structured.
Can we start with one workflow?+
Yes. The best first project is usually one repeatable file-to-output workflow with real examples, clear validation needs, and one useful downstream output.
Start a project
Tell us about the files you need cleaned, structured, or prepared.
Share the files, exports, reports, or spreadsheets your team works with, and what the cleaned output needs to be used for.