You will get Excel Data Cleaning & Formatting
Project details
I will clean, organize, and format your dataset to ensure it’s error-free, duplicates are removed, and columns are well-structured for analysis or reporting. Suitable for small, medium, or large datasets.
Data Tool
Microsoft ExcelWhat's included
| Service Tiers |
Starter
$10
|
Standard
$25
|
Advanced
$60
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 6 days |
Number of Revisions | Unlimited | Unlimited | Unlimited |
Number of Pages Mined/Scraped | 1 | 3 | 5 |
Number of Sources Mined/Scraped | 1 | 2 | 3 |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$2 - $10About Mohamad Hafiszudin
Data Analysis, Data Cleaning, Data Visualization
Kota Tinggi, Malaysia - 11:39 am local time
I help individuals and businesses turn raw data into clear, meaningful insights that support better decision-making.
I specialize in:
📊 Data Analysis & Visualization (Excel, Power BI, SQL, Tableau)
🧹 Data Cleaning & Transformation to improve data quality
📈 Dashboard & Report Creation for business performance tracking
🔍 Exploratory Data Analysis (EDA) to uncover trends and patterns
With hands-on experience in real projects such as analytics dashboards, reporting systems, and data-driven case studies, I focus on delivering work that is:
- Clear
- Accurate
- On time
- Easy to understand
I’m currently building my career as a freelance data analyst, continuously improving my skills through projects and professional certifications.
Steps for completing your project
After purchasing the project, send requirements so Mohamad Hafiszudin can start the project.
Delivery time starts when Mohamad Hafiszudin receives requirements from you.
Mohamad Hafiszudin works on your project following the steps below.
Revisions may occur after the delivery date.
Understand the Dataset
Identify dataset type (Excel, CSV, SQL export). Check number of rows, columns, duplicates, and missing values.
Data Cleaning
Remove duplicate rows. Handle missing or null values (replace, fill, or delete). Correct formatting (dates, numbers, text). Standardize column names and types.