You will get a clean and normalized data for a agile, focused and clear analytics
Project details
Need to clean and normalize messy business data for reporting, dashboards, or analytics? I offer structured, per-project data cleaning services tailored to your scope.
Whether you're a small business with a few spreadsheets or an enterprise with multi-source datasets, I’ll transform your raw data into clean, consistent, and analysis-ready formats.
Services include duplicate removal, format standardization, schema alignment, and multi-source reconciliation.
Choose from three tiers: Starter (quick cleanup), Standard (multi-source normalization), or Advanced (deep cleaning with schema mapping and support).
Delivery includes cleaned files, schema maps, and optional visual summaries. Let’s turn your data chaos into clarity.
Whether you're a small business with a few spreadsheets or an enterprise with multi-source datasets, I’ll transform your raw data into clean, consistent, and analysis-ready formats.
Services include duplicate removal, format standardization, schema alignment, and multi-source reconciliation.
Choose from three tiers: Starter (quick cleanup), Standard (multi-source normalization), or Advanced (deep cleaning with schema mapping and support).
Delivery includes cleaned files, schema maps, and optional visual summaries. Let’s turn your data chaos into clarity.
Data Tool
PythonWhat's included
| Service Tiers |
Starter
$250
|
Standard
$500
|
Advanced
$900
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Pages Mined/Scraped | 10 | 25 | 50 |
Number of Sources Mined/Scraped | 2 | 5 | 10 |
Frequently asked questions
About Aimmaz
An ETL developer delivering insights for agility, focus and clarity.
Vaughan, Canada - 6:06 pm local time
His career began in chemical engineering and process research at Tesla, where he supported cell manufacturing experiments, optimized pilot processes, and worked hands-on with production data. That foundation in analytical rigor and troubleshooting now informs his consulting work in Data & AI at Avanade.
He has spent several years designing, operating, and improving analytical infrastructure for an insurance client serving the mortgage default sector—strengthening pipelines, models, catalogues, governance, and DevOps practices so insights flow cleanly and decisions move faster.Across industries, his approach remains steady, composed, and precise.
Through his brand "aimmaz", he delivers analytics that sharpen agility, focus, and clarity—enabling businesses to understand their resources, protect financial health, and act with confidence.
Steps for completing your project
After purchasing the project, send requirements so Aimmaz can start the project.
Delivery time starts when Aimmaz receives requirements from you.
Aimmaz works on your project following the steps below.
Revisions may occur after the delivery date.
1. Client Onboarding & Scope Definition
Define scope, data formats, and goals. Starter uses a quick intake; Standard and Advanced include sample files and schema alignment.
2. Data Acquisition
Collect data from defined sources. Starter handles 10 pages/2 sources; Advanced supports up to 50 pages/10 sources.