You will get cleaned, matched and reconstructed datasets
Project details
Built a Python-based data reconstruction pipeline designed to clean, normalize, match and consolidate information coming from multiple inconsistent datasets.
The project simulates a common business scenario where customer records, sales transactions and support tickets exist across disconnected files with different formats, naming conventions and data quality issues.
The pipeline automatically:
• Cleans raw data
• Normalizes customer names
• Matches entities across sources
• Reconstructs customer profiles
• Generates reconciliation metrics
• Produces a unified master dataset
This approach reduces manual reconciliation work and creates a reliable single source of truth for reporting, analytics and operational decision-making.
The project simulates a common business scenario where customer records, sales transactions and support tickets exist across disconnected files with different formats, naming conventions and data quality issues.
The pipeline automatically:
• Cleans raw data
• Normalizes customer names
• Matches entities across sources
• Reconstructs customer profiles
• Generates reconciliation metrics
• Produces a unified master dataset
This approach reduces manual reconciliation work and creates a reliable single source of truth for reporting, analytics and operational decision-making.
Data Tool
PythonWhat's included
| Service Tiers |
Starter
$25
|
Standard
$80
|
Advanced
$180
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Pages Mined/Scraped | 1000 | 5000 | 10000 |
Number of Sources Mined/Scraped | 1 | 3 | 5 |
Optional add-ons
You can add these on the next page.
Additional Revision
+$10
Additional Page Mined/Scraped
+$15
Additional Source Mined/Scraped
(+ 1 Day)
+$20Frequently asked questions
About Aylin
Automating Reports, Documents and Data Workflows with Python
Iquique, Chile - 11:35 am local time
My experience includes OCR pipelines, automated PDF reporting, document intelligence, traceability systems, Excel automation and business process automation.
Technologies: Python, OCR, Excel, Power BI, PDF Processing, Data Analysis and Workflow Automation.
Steps for completing your project
After purchasing the project, send requirements so Aylin can start the project.
Delivery time starts when Aylin receives requirements from you.
Aylin works on your project following the steps below.
Revisions may occur after the delivery date.
Upload Your Files
Send the Excel or CSV files that need cleaning, matching or reconstruction.
Data Assessment
I review the datasets, identify inconsistencies and define the reconstruction approach.