80% of data science is just cleaning. Here is how to do it right. 🧹📊

Most beginners rush to build models, but seasoned experts know the real work happens before the training starts. If your data is messy, your advanced algorithms are useless.

This guide breaks down the two biggest enemies of clean data:

1⃣ Missing Values: These create gaps and bias. You can fix them by removing rows or filling them with the mean, median, or mode.

🔢 Outliers: Extreme values that distort reality. Detect them using Z-scores or IQR, then cap or transform them.

The Payoff: In real-world projects, proper cleaning can boost model accuracy by 8% or more.

💡 Pro Tip: Always visualize your data first. A simple plot often reveals issues that raw numbers hide.

🔅 Excel Data Analysis for Supply Chain: Forecasting

📝 Master Excel-based supply chain forecasting techniques to make data-driven decisions and improve operational efficiency.

🌐 Author: Eddie Davila
🔰 Level: Intermediate
⏰ Duration: 3h 37m

📋 Topics: Supply Chain Management, Data Analysis, Microsoft Excel

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📱Data Science
📱Excel Data Analysis for Supply Chain: Forecasting

📱Data Science
📱Excel Data Analysis for Supply Chain: Forecasting

📱Data Science
📱Excel Data Analysis for Supply Chain: Forecasting

📱Data Science
📱Excel Data Analysis for Supply Chain: Forecasting

📱Data Science
📱Excel Data Analysis for Supply Chain: Forecasting

📱Data Science
📱Excel Data Analysis for Supply Chain: Forecasting

📱Data Science
📱Excel Data Analysis for Supply Chain: Forecasting

📱Data Science
📱Excel Data Analysis for Supply Chain: Forecasting

📱Data Science
📱Excel Data Analysis for Supply Chain: Forecasting

📱Data Science
📱Excel Data Analysis for Supply Chain: Forecasting

📱Data Science
📱Excel Data Analysis for Supply Chain: Forecasting

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