Data Conversion Outsourcing · From $7/hour

Outsourced Data Conversion Services for Files, Documents and Databases

Convert CSV, Excel, XML, JSON, PDF and database exports into validated target formats. Your dedicated team maps fields, handles exceptions and reconciles the output against agreed acceptance rules.

$0/hr
Starting rate
0 days
To deployment
0+
Active clients
0.5%
Accuracy SLA
ISO 27001ISO 27001
ISO 9001ISO 9001:2015
GDPRGDPR Ready

Where data conversion projects usually break

Changing a file extension is easy. Preserving field meaning, relationships and control totals is the real work.

The same field follows different rules across files

Dates, currencies, identifiers and blank values often vary by source. We profile representative files before the full run so hidden patterns become written rules.

  • Inventory source formats, record counts and encodings
  • Document date, currency, unit and null-value rules
  • Separate correctable records from business exceptions
  • Approve a representative pilot before production
Inconsistent Sources visual

Data conversion work measured by the output

Verified delivery evidence, not generic accuracy claims.

What our data conversion service includes

Scope is built around your source, target and acceptance rules. We do not force every project into the same workflow.

Source profiling

File types, volumes, fields, encodings, duplicates and missing-value patterns.

Field mapping

Source-to-target rules for fields, codes, defaults, relationships and exclusions.

Format conversion

CSV, XLSX, XML, JSON, PDF, HTML, SQL exports and documented flat files.

Human exception review

Manual handling for OCR errors, ambiguous records and rules automation cannot resolve.

Validation and reconciliation

Counts, required fields, relationships, rejected rows and control totals.

Delivery documentation

Mapping version, output files, exception log and acceptance evidence.

Source-to-target controls

What must be defined before data conversion starts

The conversion plan connects each source type to a target rule, exception owner and measurable acceptance check.

Data conversion sources, targets, preparation steps, validation controls and delivery evidence.
SourceTargetPreparationValidationDelivery evidence
CSV or ExcelERP or CRM import fileNormalize headers, dates, codes and required fieldsRow counts, required fields, rejected-record reviewApproved mapping, output file and exception log
XML or JSONNew schema or API payloadMap nested objects, keys, arrays and value rulesSchema validation, relationship checks and sample queriesMapping version, validation results and accepted exceptions
PDF or scanned imageSearchable PDF, CSV, XLSX or JSONDefine document classes, fields and OCR thresholdsSource-image sampling, confidence review and control totalsStructured output, source references and review log
SQL export or legacy tableTarget database or application schemaProfile data types, keys, encodings and dependenciesRecord counts, relationship integrity and business totalsConverted dataset, reconciliation report and issue register

Conversion workflow

Keep source records, mapping rules and QA evidence connected

A defensible conversion does not jump directly from an input file to a finished export. The team profiles the source, applies approved mapping rules, isolates exceptions and reconciles the target before acceptance.

Representative workflow. The exact fields, checks and owners are defined from your source sample and target requirements.

Data conversion workflow showing source records mapped into a validated target data structure with exception and quality checks

Test the conversion before committing the full dataset

Send a representative source sample and target template. We will identify mapping, exception and validation requirements before production.

No commitment required. We respond within 24 hours.

$7/hr
Starting rate
99.5%
Accuracy SLA
7 days
Team deployment
ISO
27001 and 9001:2015

When outsourced data conversion makes sense

A service provider should remove repeatable work without taking business decisions away from your team.

High volume

Your internal team is buried in repetitive conversion work

We assign a dedicated team to documented batches while your data owners retain control of mappings and exceptions.

Scope the workload
Messy sources

Automation handles the easy records but misses the exceptions

We combine approved tools with human review, so difficult documents and inconsistent records do not disappear from the workflow.

Review a sample
Audit pressure

You need evidence that the target matches the source

The handoff includes reconciliation results, rejected-record logs and the approved mapping version, not only a converted file.

Define acceptance checks

How the data conversion process works

1

Audit the source

Confirm formats, volumes, quality issues, sensitive fields and the business purpose of the target output.

2

Map the target

Document field mappings, value translations, defaults, exclusions and ownership for ambiguous records.

3

Run a pilot

Convert a representative batch containing normal records and known edge cases, then refine the rules.

4

Convert in controlled batches

Process approved batches, apply documented transformations and keep exceptions visible for review.

5

Validate and deliver

Reconcile counts, required fields, relationships and control totals before delivering files and evidence.

What clients say about working with Acelerar

We needed reliable, fast data entry at scale. Acelerar delivered consistent quality from day one, no ramp-up time needed.

Data conversion services: common questions

A data conversion service changes information from one format, structure or schema into another, then checks that the target output remains complete and usable. The work can include profiling, mapping, cleansing, conversion, exception handling and reconciliation.
Common inputs include CSV, XLSX, XML, JSON, PDF, HTML, SQL exports and documented flat files. Legacy or proprietary formats require a source sample, available documentation and a target-schema review before we confirm feasibility.
Checks are agreed before production and may include record counts, required fields, duplicate review, relationship integrity, schema validation, rejected-row logs and control-total reconciliation. Acelerar offers a 99.5% accuracy SLA for agreed fields and rules.
Timing depends on volume, source consistency, mapping complexity, manual review, security requirements and approval cycles. A dedicated team can be deployed in 7 days, but the conversion schedule is set only after source and target review.
Acelerar teams start from $7/hour with no setup fee and month-to-month terms. The estimate is based on the actual source condition, record volume, target requirements, validation depth and deadline.
Data conversion changes format or structure. Data migration moves information between systems or environments and may include conversion as one phase. Projects involving replication, cutover or application dependencies should be scoped as migration work.
Get a Custom Quote

Show us the source and the target

Share a representative sample, required output, approximate volume and deadline. We will respond with the mapping, pilot, QA and delivery scope.

  • Response within 24 hours — no automated replies
  • Custom proposal, not a generic pricing sheet
  • $7/hr starting rate, no long-term contracts
  • ISO 27001 certified — your data stays yours

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