I will do data cleaning, data formatting, data management

Data Projects are 80% Data Cleaning , 20% Dashboarding, Modelling, Driving Insights, & Informing Decisions.

Wrong Data = wrong Analysis.

Hence, Data cleaning is very important.

Dirty data significantly impact business operations, so you must ensure your datasets are clean for analysis and visualization.

Data Cleaning comes before Analysis & Visualization.

My Data Cleaning Process:

1. Handle missing values

2. Remove duplicates carefully

3. Standardize formats

4. Fix data types

5. Handle outliers properly

6. Validate the data

7. Trim and clean text fields

8. Create consistent categories

9. Document my cleaning steps

10. Review the entire datasets

If you have datasets that need cleaning before carrying out your analysis, you can reach out to me.

Please send a brief about the project before we proceed with the project.