You will get Advanced Text List Comparison (Data Matching and Duplication Check)
Project details
I offer an effective Python-based solution for analyzing and comparing textual data, which enables you to:
• identify duplicates, organize and, if necessary, cleanse the database;
• uncover unique entries.
It is ideally suited for tasks requiring complex text comparisons. For instance, when it's necessary to identify entries like «John Smith» and «J. Smith», «john smith», «Jhon Smith», or «JohnSmith».
Applications:
• CRM systems (names, addresses);
• inventory management systems (product names, SKUs);
• Internet marketing (search queries, SEO keywords);
and so on.
Why Excel Is Not Sufficient:
• Limited search capabilities (only fully identical records).
• Difficulty in handling large volumes of data.
The result will be presented in the form of original lists augmented with columns containing categorical markers.
For comparisons:
• within a single list - Duplicate (full match) / Duplicate (most likely) / Non-Duplicate;
• between different lists - Match (full) / Match (most likely) / Mismatch;
as well as diagrams visually representing the ratio of the listed categories.
This tool can significantly simplify the process of comparing lists and accelerate informed decision-making.
• identify duplicates, organize and, if necessary, cleanse the database;
• uncover unique entries.
It is ideally suited for tasks requiring complex text comparisons. For instance, when it's necessary to identify entries like «John Smith» and «J. Smith», «john smith», «Jhon Smith», or «JohnSmith».
Applications:
• CRM systems (names, addresses);
• inventory management systems (product names, SKUs);
• Internet marketing (search queries, SEO keywords);
and so on.
Why Excel Is Not Sufficient:
• Limited search capabilities (only fully identical records).
• Difficulty in handling large volumes of data.
The result will be presented in the form of original lists augmented with columns containing categorical markers.
For comparisons:
• within a single list - Duplicate (full match) / Duplicate (most likely) / Non-Duplicate;
• between different lists - Match (full) / Match (most likely) / Mismatch;
as well as diagrams visually representing the ratio of the listed categories.
This tool can significantly simplify the process of comparing lists and accelerate informed decision-making.
Purpose
PersonalIndustry
Data Analytics, Ecommerce, Education, Events Planning, Financial Services, Real Estate, Retail & WholesaleLanguage
EnglishWhat's included
| Service Tiers |
Starter
$5
|
Standard
$10
|
Advanced
$20
|
|---|---|---|---|
| Delivery Time | 3 days | 3 days | 3 days |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$10 - $40About Andrei
Excel Modeling || Data analysis || Web scraping || Python
Kutaisi, Georgia - 9:00 pm local time
I have over 15 years of experience working in financial organisations and consulting firms as a property valuation expert. This role involves regular data collection and analysis, as well as the development of financial and mathematical models based on this information. So I am highly proficient in Excel (formulas, pivot tables, dashboards, macros) and Google Sheets for data analysis. Additionally, I possess programming skills in Python.
I will be glad to be of help to you.
Steps for completing your project
After purchasing the project, send requirements so Andrei can start the project.
Delivery time starts when Andrei receives requirements from you.
Andrei works on your project following the steps below.
Revisions may occur after the delivery date.
Initial Data Review and Consultation
The data is first reviewed to understand its structure and specific requirements.
Preliminary Data Processing
The data is prepared for analysis, ensuring readiness for the next stages.