Auto Parts Data Cleanup

@hdlan

Hi, I am a skilled Excel professional from Vietnam with 25+ years of experience. I can help you format and convert your data. Specifically, I can split product descriptions into multiple 4 relevant columns. I am currently available and ready to commence work immediately. How can I help you with your Excel task? Best regards, Duong

@imraz2016

Hi There, I have strong experience with Excel data cleanup, product catalog migration, Power Query, regex-based parsing, and handling inconsistent product descriptions. I can move each vendor catalog into your master structure, extract Year / Make / Model into separate columns, clean the description field without removing unrelated text, and provide a review log for any ambiguous rows.

@ShaikhAneesa

Hi there, I understand you need five incoming auto-parts vendor workbooks transformed into clean, consistent Excel catalogs, with the Year, Make, and Model extracted from inconsistent product descriptions and placed into dedicated columns without damaging the remaining product information. I’m confident I can handle the variation across vendors systematically while flagging genuine edge cases for review. My approach is to first profile each vendor’s description patterns, then build a controlled extraction process using Excel Power Query, VBA, formulas and regex-style pattern logic where appropriate. Vehicle references will be separated into Year, Make and Model fields, while the original description is cleaned without losing relevant product details. Vendor-specific patterns will be handled through reusable rules rather than relying on fragile search-and-replace. I’ll validate the cleaned rows against the source workbooks, check extraction accuracy and formatting, and provide a concise exception log containing only records that require your confirmation. Each vendor will receive a fully populated, independently usable Excel file. Could you provide a small sample from each vendor showing the typical description patterns so I can assess the extraction complexity and give you a reliable per-line estimate? I’m ready to start immediately. Warm Regards, Aneesa.

@asifdwan

Hi, I can handle the five vendor catalogs using Excel/Power Query and Python/regex where helpful. I’ll extract Year, Make, and Model from the varied descriptions, remove only the vehicle-specific text, and preserve the remaining descriptions accurately. I’ll deliver one cleaned Excel file per vendor plus a short log of uncertain/edge-case rows for review. I can start next week and dedicate 30–40 hours in the first week. I’m happy to review sample rows first and then provide a firm estimate.

@tmoi06

Hello Sir, I can handle the five auto-parts vendor workbooks and accurately transfer their catalogs into your required master structure while separating Year, Make, and Model from the product descriptions. ✅ Why Me? ✔ Extensive experience in Excel data processing, automotive product catalogs, data cleaning, product matching, and large-scale spreadsheet management ✔ Strong experience handling inconsistent product descriptions and extracting structured information from semi-structured text ✔ Skilled with Excel formulas, Power Query, VBA, and regex/Python-assisted workflows for repetitive data-processing tasks ✔ Strong attention to detail when working with vehicle fitment information such as Year, Make, and Model ✔ Able to preserve the original product description while removing only the vehicle-specific information that belongs in the dedicated columns ✔ Strong quality-control process for checking extracted fields against the original descriptions ✔ 500+ projects completed | 5.0-star rating I understand that this is not a simple find-and-replace task because the five vendors may use different description patterns. If you provide a small sample from each vendor, I can first establish the extraction logic and confirm the expected Year/Make/Model treatment before processing the full five workbooks. Best regards, Ayan

@EightVeer

Hi there, We will clean the five vendor Excel workbooks, split each product description into Year, Make, and Model columns, and return the trimmed descriptions plus a brief exception log for any ambiguous rows. We can also use Excel functions, Power Query, or VBA/regex-style logic where it best preserves the rest of the text. We have public Freelancer review history covering AI adoption, data management and analytical engagements. Could you share one sample vendor sheet so we can confirm the recurring description patterns before we start? This first workstream is limited to data review, quantitative analysis and prioritised findings for Auto Parts Data Cleanup. Broader implementation would be scoped separately on Freelancer. Best Regards, 8veer

@zafarfarooq612

Hello, I can accurately transfer all five vendor catalogs into your required format while extracting Year, Make, and Model from inconsistent product descriptions and preserving the remaining description text. I can use Excel/Power Query or regex-based methods where appropriate, with manual checks for edge cases, and provide a clear uncertainty log for your review. I can start next week, dedicate 30–40 hours in the first week, and my rate is $2/hour. Regards, Zafar

@mattafareed4848

Hello I understand the requirements and can carefully process each vendor workbook, separating Year, Make, and Model while preserving the original product descriptions. I can start next week, dedicate consistent hours, and provide cleaned files plus a clear log of any uncertain rows. My rate is $5/hour. Regards Muhammad

@asifkhan268

Hi, I’d be happy to help with this project. I have previously worked on Year / Make / Model-related data projects, including cleaning and separating vehicle information from product descriptions, so I’m familiar with the attention to detail this requires. I can carefully process each vendor’s Excel workbook, extract the Year, Make, and Model into dedicated columns, and clean the descriptions without removing important product information. I can use Excel functions, Power Query, or other suitable methods depending on the patterns in the source data. I’ll also maintain a brief log of any uncertain rows for your review. I can start immediately whenever you want and can commit around 25–30 hours during the first week. My rate is $4/hour (or I can provide a per-line rate once I see a few sample rows). I’m happy to review sample data beforehand so I can confirm the approach and give you a more accurate estimate. Best regards, Karim

@techplusintl

The main challenge here is accurately extracting the 'Year / Make / Model' data from inconsistent product descriptions without losing critical information. Given the variability in the source data, a combination of Excel functions and possibly VBA or regex will be essential to ensure precision. I would start by analyzing a few sample rows to identify patterns and then develop a systematic approach to clean each vendor's catalog. This will include creating dedicated columns for Year, Make, and Model while maintaining the integrity of the remaining description. I can start immediately and estimate around 15 hours in the first week to ensure thoroughness in the data processing.

@Sumyasuma

Hi, I can handle all five vendor Excel catalogs and accurately separate the **Year, Make, and Model** from each product description while keeping the remaining description clean. I’ll use Excel/Power Query, regex, and manual checking for inconsistent patterns and edge cases. I’ll also provide a short review log for any uncertain rows. I can start next week and dedicate **50+ hours during the first week**. I’m comfortable with either hourly or per-line pricing. Please send a few sample rows so I can confirm the extraction method and estimate the workload accurately.

@sagarwal3005

Cleaning up data from multiple auto-parts vendors while ensuring the correct extraction of “Year, Make, Model” from varying descriptions is a task that requires both precision and attention to detail. I can leverage my expertise in Excel automation and data processing to efficiently isolate and extract the required information using advanced Excel functions and VBA. I excel in managing complex data manipulations and have a strong track record in similar tasks. My skills in Excel and data processing align perfectly with your project requirements. With a 4.9-star rating across 200 client reviews and 220 projects completed, you can trust in my ability to deliver high-quality results. When would you like to start this project, and could you provide an estimate of the total volume of data to be processed?

@kishwariqbal767

Hi, I’m **Kishwar Iqbal**, experienced in Excel data entry, data cleaning, and product catalog management. I can accurately extract **Year, Make, and Model** from inconsistent descriptions while preserving all other product information. I can use Excel functions, Power Query, or regex-based methods where appropriate, followed by manual checks for accuracy. I’ll also provide a clear log of any uncertain rows. I’m available to start next week and can dedicate consistent hours during the first week. **Best regards, Kishwar Iqbal**

@mahisha123

As an experienced professional, I am no stranger to the challenges your project entails. I have extensive expertise in data processing and automation tools such as Excel functions, Power Query, VBA and regex-driven tools which will prove invaluable in identifying and separating the Year, Make, and Model data from the product descriptions. My proven track record of detail-oriented work speaks for itself in my 100+ projects where I've consistently provided reliable, accurate and results-driven virtual assistance tailored to each client's business goals. In addition to my technical prowess with different data tools, I also bring a business understanding having two key degrees in HR, Marketing and Computer Applications; giving me a unique advantage in understanding your specific needs. My MBA taught me how attention to detail is crucial as it means that not a single important piece of data will fall through the cracks. My commitment to long-term collaboration combined with my strong communication skills guarantees us seamless coordination throughout the project lifecycle. I know your time is valuable so I vow to deliver on or ahead of schedule without compromising on quality. Given the opportunity, my dedication would greatly align with your project goals ensuring it is completed accurately and efficiently.

@Fazeennazar

Hello, With over 7 years as a senior engineer, I'm confident I am the best candidate for your auto-parts data cleanup project. My extensive skillset, specifically in Data Analysis and Data Processing combined with my experience with Excel Macros, VBA and other ETL tools like Power Query will ensure that your project is handled with maximum efficiency and attention to detail. I understand that parsing inconsistent data in thousands of rows require more than simple search-and-replace functions. It calls for a careful approach which I have honed over the years in various projects. My familiarity with Python, Pandas and Regular Expressions make me well-suited to handling your task of stripping vehicle-specific data from product descriptions. I can use my skills to smoothly move each vendor's catalog into your master sheet ensuring that your new columns are accurately populated without damaging the rest of the text. Furthermore, my proficiency in web scraping using libraries like Beautifulsoup, Selenium etc can come handy if needed. Finally, as a full-time freelancer ready to dedicate myself solely to your project right away, you can expect your deliverables on time or even before scheduled. On completion, I'll also provide you a brief log of any rows I'm unsure about for quick review. Choose me for timely delivery, impeccable work quality and most importantly, let's build towards a successful project together! Thanks!

@moustafa1

Hello, I’d be happy to help with this project. I have experience working with Excel data cleanup, organization, and structured data extraction, and I understand that the main challenge here is accurately identifying Year / Make / Model information even when vendor descriptions use inconsistent formats. I’ll carefully review the source workbooks, transfer the catalog information into the required format, separate the Year, Make, and Model into their dedicated columns, and remove that vehicle-specific information from the product descriptions without altering the remaining text. Please send me a message through chat to discuss the website and your preferred format so we can get started. Best regards, Moustafa

@faisal702

Hello, I can accurately clean and merge each vendor catalog, extract Year/Make/Model from inconsistent descriptions using Excel/Power Query/regex where appropriate, and flag uncertain rows for review. I’m available to start next week and can dedicate flexible hours during the first week; I’m happy to agree on either an hourly or per-line rate after reviewing a sample.

@ImranAli01

Hi there, I got that you need five auto-parts vendor workbooks cleaned and consolidated, with inconsistent Year/Make/Model references accurately extracted into dedicated columns while keeping descriptions free of vehicle-specific data. This is what I can help you with, let's chat. My approach is to use Excel Power Query, VBA, and targeted regex logic to identify recurring Year/Make/Model patterns, handle inconsistent descriptions, preserve the remaining product text, and flag uncertain rows instead of making risky assumptions. I’ll validate extracted fields against the source rows and deliver clean, review-ready workbooks. As final deliverables you will receive one fully cleaned Excel file per vendor, populated Year, Make, Model, and description columns, plus a concise exception log highlighting every uncertain or ambiguous row. I can start next week and dedicate focused hours during the first week based on your volume. Please send a few representative sample rows so I can confirm the extraction logic and give you an accurate hourly or per-line estimate. Regards, Imran S.

@thewebscraper

I can devote 10 hours for the first week and hourly rate is $35. I can efficiently cleanup all your vendor data.