How to Clean & Integrate Data Like a Pro (SQL Demo Inside)

Data quality is crucial for reliable insights, and even the best SQL skills can't compensate for messy data. This episode highlights common data issues and offers practical solutions for data cleaning. Using SQL, pandas, and dateutil, learn how to identify and rectify problems, ensuring your data is trustworthy. #DataCleaning #SQLTutorial #PythonPandas #DataQuality #DataWranglingLearn how to clean your data like a pro with these powerful SQL tricks! In this video, we'll dive into the world of data cleaning and show you how to use SQL to remove duplicates, handle missing values, and perform data normalization. Whether you're a data analyst, scientist, or engineer, these SQL tips and tricks will help you to work more efficiently and effectively with your data. From string manipulation to data aggregation, we'll cover it all. So, if you're ready to take your data cleaning skills to the next level, watch this video now and start cleaning your data like a pro!

00:00 Introduction to Data Quality Issues
01:20 Creating a Mess on Purpose
02:45 SQL-Based Cleaning: Strings That Behave
04:01 Cleaning Dates with Date Util
04:55 Gender Normalization Techniques
05:45 Why Data Cleaning Matters for Integration
06:40 Protecting the Data Pipeline
07:08 Recap and Final Thoughts