Spreadsheet Data Cleanup and QA for Analysis-Ready Datasets

Spreadsheet Data Cleanup and QA for Analysis-Ready DatasetsSpreadsheet Data Cleanup and QA for Analysis-Ready Datasets

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Talal Alathel

• Sep 26

Concept Project — Data Cleanup & QA

A practical example of turning inconsistent spreadsheet data into a clean, structured, analysis-ready dataset using validation rules, duplicate checks, standardized formats, and a final QA pass.

Data Analysis Microsoft Excel

Rooney Kibet

• Sep 27

BEFORE: Client had messy Excel inventory with 500 rows, duplicates (A12 / a12), blanks, wrong prices like "$ 2.5" and "N/A", and different warehouse names (KER / ker / Kericho).

AFTER: I did:

Removed 12 duplicate SKUs

Standardized item names to Title Case

Fixed QTY and Prices to 2 decimals

Unified Warehouse to Kericho

Made sheet ready for pivot dashboard

Result: Clean, ready-to-use inventory in 2 days using Excel.

Tools: Excel, Remove Duplicates, Text to Columns, TRIM, PROPER

Data Analysis Microsoft Excel

Nency Purohit

• Sep 27

Cleaned and formatted a raw dataset in Excel by removing duplicates, fixing formatting issues, handling missing values, and organizing the data into a structured format for analysis.

Data Analysis Microsoft Excel

Syed Abdul Qadir Gilani

• Sep 27

A sample Python project showing my data cleaning workflow — removing duplicates, handling missing values, standardizing text fields, and summarizing sales by city using Pandas. This reflects the kind of cleanup and analysis I do for client datasets.