What is Data Cleaning & Pre processing?

Data Cleaning & Pre processing is the process of preparing raw data for analysis by identifying and correcting errors, inconsistencies, and missing values.

Key Tasks

✔ Removing duplicate records ✔ Handling missing values ✔ Correcting data entry errors ✔ Standardizing formats (dates, text, numbers) ✔ Removing irrelevant data ✔ Detecting and treating outliers ✔ Transforming data into a usable format

Example

Raw data may contain duplicate entries, missing values, incorrect formats, or inconsistent information. **Data cleaning** fixes these issues to make the data accurate and ready for analysis.

Why is it Important?

✔ Improves data quality ✔ Increases analysis accuracy ✔ Reduces errors in reports and dashboards ✔ Helps create reliable machine learning models

Data Cleaning & Preprocessing is a crucial step in **Data Analytics**, Data Science, and Machine Learning because high-quality data leads to better insights and decision-making.