🔍 Data Analytics vs Data Science – Key Differences Explained

These two fields often get mixed up, but here’s how they truly differ 👇

📊 Data Analytics

• Examines structured datasets
• Uses tools like SQL, Excel, Power BI, Tableau
• Focuses on descriptive (what happened) & diagnostic (why it happened) insights
• Helps businesses improve processes & make informed decisions

🤖 Data Science

• Works with structured + unstructured data
• Uses Python, R, TensorFlow, Machine Learning models
• Focuses on predictive (what’s likely to happen) & prescriptive (what should be done) insights
• Builds AI-driven solutions & forecasts trends

💡 Think of it this way:
➡️ Data Analytics looks into the past to explain the present.
➡️ Data Science predicts the future and creates intelligent solutions.

🚀 Both are essential for modern businesses – Analytics sharpens today’s decisions, while Science designs tomorrow’s opportunities.

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