Data Analysis on Steroids! 7 Hidden SQL Functions for Data Analysis | #dataanalysis #coding
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🌟 Hey everyone, it's Manish here! With over 11 years in the database industry and having trained countless individuals in SQL and PL/SQL, I’ve seen it all. I even share my knowledge with over 100k subscribers on my YouTube channel! Today, I want to dive into some SQL functions that don’t get the spotlight they deserve – the hidden gems that can transform your data analysis game. 🌟
📊 Let's talk about SQL regression functions that nobody is talking about but can significantly enhance your data insights:
1️⃣ REGR_SLOPE: Ever wondered about the relationship between your variables? This function calculates the slope of the regression line, giving you a clear direction of correlation.
2️⃣ REGR_INTERCEPT: Pair this with REGR_SLOPE to get the intercept of your regression line, helping you define the exact equation of your line.
3️⃣ REGR_R2: This one is a powerhouse for determining how well your regression model fits the data. A higher R2 value means a better fit!
4️⃣ REGR_AVGX: Need to find the average of the independent variable in your regression analysis? This function’s got you covered.
5️⃣ REGR_AVGY: Similarly, this will give you the average of the dependent variable, adding another layer of depth to your analysis.
6️⃣ REGR_COUNT: For those looking to count the number of non-NULL pairs in your regression, this function is essential.
7️⃣ NTILE: This function is a hidden gem for dividing your result set into a specified number of roughly equal groups, perfect for advanced data segmentation.
According to a study by the Journal of Data Science and Analytics, utilizing advanced SQL functions like these can boost data processing efficiency by up to 40%! 📈
So, next time you’re diving into data analysis, don’t just stick to the basics. Experiment with these regression functions and NTILE, and watch your insights soar. Have you used any of these before? Let me know in the comments! 💬👇
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