Clean up inconsistent Excel, Google Sheets and CSV files before reporting, analysis, import or handoff. Rudrriv can remove duplicates, standardize dates and numbers, tidy text, organize worksheets and review obvious data-quality issues within an agreed cleanup rule set.
Final scope depends on workbook size, number of sheets, formula complexity, duplicate rules and the cleanup standards you want applied.
| Account | Date | Region | Amount |
|---|---|---|---|
| acme ltd | 1/2/26 | north | $1,250 |
| Acme Ltd | 2026-02-01 | North | 1250.00 |
| NOVA CO. | 02-03-2026 | SOUTH | 980 |
| Nova Co. | 2026-03-02 | South | 980.00 |
Plans are organized around workbook size and cleanup depth. Start with a defined package when the problem is clear, or request a custom scope for multiple files, recurring exports or specialized data rules.
For a small spreadsheet that needs a focused cleanup before sharing, filtering or basic analysis.
One-time service
For operational workbooks with several sheets, inconsistent fields and repeated formatting issues.
One-time service
For larger files that need broader consistency checks, documented issues and a more structured QA pass.
One-time service
Scope note: Pricing assumes the source data can be opened and reviewed normally. Password-protected files, damaged workbooks, very large datasets, complex macros, extensive formula repair, data enrichment or manual verification against external sources may require a custom estimate.
Get in touch with our expert. Tell us what you need, and we'll help identify the most suitable service, scope and pricing for your requirement.
Each project starts by defining what should change and what must stay untouched, then moves through cleanup, verification and final delivery.
Review workbook type, sheet count, size and known data issues.
Confirm date, number, text, duplicate and formatting standards.
Apply agreed cleanup rules to the in-scope rows, columns and sheets.
Align labels, field order and visual formatting where required.
Check samples, duplicates, formats and obvious inconsistencies.
Return the cleaned file plus notes included in the selected scope.
The service focuses on repeatable cleanup rules that make workbooks easier to review and use without pretending to resolve business-judgment questions automatically.
Remove exact duplicates or apply agreed matching fields when duplicate logic is more specific.
Trim extra spaces, normalize obvious casing patterns and clean inconsistent text presentation.
Standardize agreed date and numeric formats so fields behave more consistently in filters and reports.
Make column names and worksheet structure easier to understand and reuse within the approved scope.
Identify blanks, malformed entries or out-of-pattern values and either clean or flag them according to the rule set.
Reduce distracting format inconsistencies and improve the visual organization of the cleaned workbook.
Good cleanup is not just deleting anything that looks unusual. These inputs help distinguish a real data error from a legitimate exception.
Define whether a duplicate means identical rows or a match on selected fields such as email, invoice number or product code.
Tell us the target convention for dates, currency, decimals, text casing and any other fields that must stay consistent.
Identify protected formulas, macros, named ranges, hidden sheets, links or other workbook features that are outside the cleanup scope.
Deliverables are structured around the selected plan so you know which file, notes and review items are included before the project starts.
An updated Excel, Google Sheets or CSV output within the agreed scope.
A concise record of the main cleanup actions where included in the selected plan.
Uncertain or business-rule-dependent entries can be called out instead of guessed.
A final consistency review across the areas covered by your package.
This comparison describes the direct operational change created by cleanup work. It does not claim specific revenue, productivity or performance improvements.
Repeated rows or records make counts and follow-up work harder to trust.
Exact or key-field duplicates are removed or flagged according to the confirmed rule set.
Different conventions make filtering, sorting and interpretation inconsistent.
In-scope date and number fields use the agreed standard across the workbook.
Names, categories or labels may look like separate values even when they represent the same thing.
Whitespace and agreed text conventions are applied consistently to in-scope fields.
Field names and layouts vary from sheet to sheet or export to export.
Headers, field order or basic organization are aligned within the approved scope.
Missing or suspicious values may be difficult for the next user to identify.
Records that cannot be safely corrected by rule can remain visible for a decision rather than being guessed.
A cleaner workbook reduces obvious friction in the next step of your workflow by making data structure, presentation and exceptions easier to understand.
Consistent fields behave more predictably when teams group, filter or review records.
Agreed duplicate rules reduce avoidable repetition in customer, product, transaction or operational lists.
Standardized sheet structure and formatting make files easier for the next person or system to interpret.
Ambiguous or suspicious values can be surfaced explicitly instead of disappearing inside a large workbook.
These are representative service-purchase scenarios only. They are not named Rudrriv customer case studies and do not claim measured business outcomes.
A business receives a recurring export with mixed date formats, inconsistent categories and repeated records before internal reporting.
A sales or support team has a spreadsheet with whitespace, repeated contacts, inconsistent country values and irregular field names.
A dataset contains inconsistent labels, blank entries and mixed number formats that need review before analysis begins.
Illustrative examples only — not actual customer identities, quotes or performance claims.
Practical answers about formats, duplicate rules, delivery, pricing, workbook protection, outputs and custom cleanup requirements.
Spreadsheet Cleanup can include duplicate removal, whitespace cleanup, consistent text casing, date and number standardization, column and row organization, formatting cleanup, obvious data-quality checks and a final quality review. The exact work depends on the selected plan and the condition of the workbook.
The service is designed for Microsoft Excel workbooks, Google Sheets and CSV or exported tabular data. If you have multiple formats, share the details in the enquiry so the scope can be confirmed before work begins.
Plans on this page start at $15 USD for a small, focused cleanup. Larger workbooks, multiple sheets, complex formulas, multiple source files or special validation rules may require a higher plan or a custom quote.
The standard delivery window for this service is 5–7 working days. Final timing depends on workbook size, number of sheets, data condition, required cleanup rules and whether clarification is needed before changes are made.
Yes, duplicate removal can be included when the rule for identifying duplicates is clear. For datasets where similar-looking records may represent different real entries, Rudrriv can flag uncertain matches instead of deleting them automatically.
Yes. The cleanup can standardize date formats, numeric presentation, text casing, spacing and other agreed formatting conventions so the workbook is easier to filter, review, import or hand off.
Only changes within the agreed cleanup scope should be made. If formulas, merged cells, named ranges, protected sheets or linked workbooks could be affected, they should be identified during intake so the cleanup rules can protect important workbook logic.
Provide the spreadsheet files or accessible sheet links, a short description of what looks wrong, any required date or number formats, known duplicate rules and any columns or formulas that must not be altered. Sensitive files can be shared through the agreed project workflow after the scope is confirmed.
Depending on the plan, you can receive the cleaned spreadsheet or workbook, an issue or change summary, flagged records that need business judgment and notes on any items that were intentionally left unchanged.
Yes. Multiple files, recurring exports and larger operational datasets can be scoped as a custom project. Tell us how often the files arrive, their approximate size and whether the same cleanup rules repeat each time.
The listed plans include a defined review round for corrections that stay within the agreed cleanup rules and source data. New cleanup rules, newly supplied files or materially expanded scope may require an updated estimate.
Choose a plan if the scope is clear, or use the enquiry form below to describe the workbook size, file format, known data issues and required output. Rudrriv can then confirm the most suitable scope, price and delivery approach.
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