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 data preparation can include.
Data Preparation is the center of the offer. A project may need one capability or several depending on the files, source structure, and output your team needs.
Data Cleansing
Fix bad, messy, duplicate, incomplete, or malformed values inside business files.
Data Standardization
Make values, formats, names, dates, categories, statuses, and fields consistent across files.
Data Mapping
Connect source fields and values to the structure needed by the next workflow.
Data Consolidation
Bring multiple spreadsheets, CSVs, exports, reports, or sources into one structured output.
Data Validation
Check required fields, missing values, duplicates, changed formats, unusual rows, and exceptions before output.
Use Cases
Where messy files slow teams down.
Data preparation usually becomes worth fixing when the same files keep coming back, the structure keeps changing, or the cleaned output feeds something important.
Project start
Discuss the recurring file workflow you want to improve.
You do not need clean data, a technical brief, or a chosen solution. A rough description of the current files, cleanup steps, and desired output is enough to start a project conversation.
The spreadsheets, CSVs, exports, PDFs, or reports involved
Whether examples are available, redacted if needed
The cleanup, mapping, consolidation, or validation steps repeated today
The clean output needed: 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. A short description of the current file problem and desired output is enough to begin the conversation.
Do we need to know the technical solution first?+
No. A short description of the current files, cleanup steps, and output your team needs is enough to begin. 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 project your team wants to discuss.
Describe the recurring files, cleanup work, review needs, and prepared output your team needs. No upload is required to start the conversation.