WHAT IS DATA CLEANING?

Data cleaning is the process of fixing messy data so it can be used properly. It involves finding and correcting errors like missing values, duplicate records, and incorrect entries to make data accurate and reliable for analysis.

Clean data = better insights and decisions.

KEY TASKS IN DATA CLEANING

1. Handling missing data
Dealing with empty or incomplete values in the dataset.

2. Removing duplicate data
Deleting repeated records that can affect results.

3. Fixing errors and typos
Correcting wrong, invalid, or inconsistent entries.

4. Standardizing data formats
Making sure dates, numbers, and units follow the same format.

5. Removing unnecessary data
Keeping only the data needed for analysis.

WHY IS DATA CLEANING IMPORTANT?

✔️ Improves data accuracy
✔️ Makes analysis more reliable
✔️ Saves time during analysis
✔️ Leads to better business decisions

Even the best analysis fails if the data is messy.

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