Improving Data Cleaning and Accuracy Skills for Better Records

Improving Data Cleaning and Accuracy Skills for Better RecordsImproving Data Cleaning and Accuracy Skills for Better Records

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Brad Peach

• 1d

Who else agrees that messy data sets are the biggest headache🧠 Data records are one of your corner posts of you business, with messy data comes messy and chaotic business.🔥 Am I the only one who continues to work and improve on skills needed to do this correctly and accurately, or do you the same.

Data Entry excel Canva Design

Malaika Shakeel

• Oct 25

A business card concept for a financial advisory brand.

For finance, I wanted the card to feel trustworthy and calm rather than flashy. A warm gold and cream palette, flowing curves at the top to add movement, and a clean contact block with simple icons so the details are easy to scan.

Gold and cream for a finance brand: classic and trustworthy, or too soft? Tell me what you think. 👇

businesscarddesign Canva Typography Canva Design Graphic Design

MD ENAYET HOSSAIN SAKIB

• Oct 26

This is a clean and elegant business card design. The soft beige and gold color palette feels sophisticated and trustworthy, which works perfectly for a financial advisor. The wave elements add a modern touch without making it look cluttered. Typography is well-balanced, and the...

Aleksandr Artiukh

• Oct 25

A personal Excel/CSV data-cleaning demo: 8 fictional input rows become 7 after removing one exact duplicate. Zero stock is preserved; a missing price stays blank and is flagged. The original data is retained for comparison. This is a self-initiated example, not client work.

I can help with Excel/CSV cleaning, reconciliation and clear reports. We agree scope, price and delivery after reviewing a sample. First project: 50% off the agreed regular quote, with no future-order commitment.

https://contra.com/p/XNEs7mLQ-excel-csv-catalog-cleanup-demo

Completed work

Data Analysis Microsoft Excel

Aroosa Mughal

• Oct 26

Great approach to data cleaning! Preserving the original data while flagging missing values and removing only exact duplicates helps maintain accuracy and transparency. These small checks can make a big difference in reliable reporting.