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Fiverr Pro
English
$
USD
I will process product catalogs and supplier spreadsheets
Data Intelligence Engineer
DataForge Lab is a South Africa-based data intelligence operation running the PSE — a proprietary, locally-hosted platform built to process raw supplier data at scale.
We transform messy, inconsistent...
About this Gig
I specialise in cleaning, structuring, and transforming messy or unorganised datasets into accurate, consistent, and usable formats. My focus is on large-scale data processing, especially product catalogs and spreadsheet-based data.
I remove duplicates, fix formatting issues, standardise fields, and restructure data into clean, reliable outputs ready for business systems, marketplaces, or internal use. Whether the data comes from multiple sources or inconsistent formats, I turn it into a structured dataset in Excel, CSV, or similar formats.
This service is ideal for e-commerce sellers, product databases, and businesses dealing with large or complex data that needs to be cleaned, normalised, and made usable. Every project is handled with attention to detail to ensure accuracy, consistency, and reliable structure.
Technology:
Excel
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Google Sheets
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Python
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VBA
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Zapier
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Alteryx
My Portfolio
FAQ
What types of data are supported?
Supported data includes structured, semi-structured, and unstructured business datasets such as spreadsheets, product catalogs, supplier feeds, logs, invoices, customer feedback, support tickets, inventory records, and mixed-format text data. Any business-related information is processed into struct
Can unstructured or messy data be processed?
Yes. The system is designed to transform unstructured and inconsistent datasets into structured, standardized formats. This includes free-text records, mixed-format entries, and datasets without predefined schemas.
What file formats are accepted?
Supported formats include Excel (.xlsx), CSV, TSV, and other delimited text files. Poorly formatted or mixed-source datasets are also supported. Sample files are recommended when unsure.
What is included in data cleaning and structuring?
Data cleaning includes removal of duplicates, correction of inconsistencies, standardisation of formats, alignment of fields, and transformation of raw data into structured, usable output.
What is the Audit Page?
The Audit Page (included in Standard and Premium packages) provides a structured summary of processing results, including duplicates removed, formatting corrections, structural changes, validation notes, and final dataset quality overview.
Are multiple datasets or sources supported?
Yes. Multi-source datasets can be merged, aligned, and standardised into a single structured output where required.
Is text-based data supported (invoices, logs, feedback, etc.)?
Yes. Free-text business data such as invoices, feedback, logs, messages, and records are interpreted and structured into usable fields where applicable.
What counts as a revision?
Revisions apply to minor adjustments within the agreed scope, such as formatting corrections or small structural refinements. Changes that expand scope or dataset size require a custom order.
What makes this different from basic data cleaning?
Processing extends beyond structured spreadsheets into unstructured and mixed-format business data, transforming complex inputs into standardized, usable datasets suitable for systems, marketplaces, and operational use.
