You can’t master modern analytics without understanding the difference between Descriptive, Diagnostic, Predictive, and Prescriptive Analytics.
Whether you're a Data Analyst, Product Analyst, Data Scientist, or just getting started in the data field, this 1-minute breakdown will give you clarity most people miss
1. ๐๐๐ฌ๐๐ซ๐ข๐ฉ๐ญ๐ข๐ฏ๐ ๐๐ง๐๐ฅ๐ฒ๐ญ๐ข๐๐ฌ - What happened?
Summarizes past data to uncover trends.
→ Data collection, cleaning, dashboards, reports.
2. ๐๐ข๐๐ ๐ง๐จ๐ฌ๐ญ๐ข๐ ๐๐ง๐๐ฅ๐ฒ๐ญ๐ข๐๐ฌ - Why did it happen?
Digs into root causes behind the numbers.
→ Drill-downs, correlation checks, hypothesis testing.
3. ๐๐ซ๐๐๐ข๐๐ญ๐ข๐ฏ๐ ๐๐ง๐๐ฅ๐ฒ๐ญ๐ข๐๐ฌ - What will happen?
Uses ML + historical data to forecast outcomes.
→ Model training, validation, performance tuning.
4. ๐๐ซ๐๐ฌ๐๐ซ๐ข๐ฉ๐ญ๐ข๐ฏ๐ ๐๐ง๐๐ฅ๐ฒ๐ญ๐ข๐s - What should we do?
Recommends actions based on predictions.
→ Optimization, simulation, decision modeling.
If you want to go deeper, start learning from these top YouTube channels:
1. ๐๐ฅ๐๐ฑ ๐๐ก๐ ๐๐ง๐๐ฅ๐ฒ๐ฌ๐ญ – https://lnkd.in/eeEMPeG6
2. ๐๐จ๐๐๐๐๐ฌ๐ข๐๐ฌ – https://lnkd.in/df4Eyb53
3. ๐๐ฎ๐ค๐ ๐๐๐ซ๐จ๐ฎ๐ฌ๐ฌ๐ – https://lnkd.in/dmbzK-zn
4. ๐๐ซ๐ข๐ฌ๐ก ๐๐๐ข๐ค – https://lnkd.in/eaqVxr57
5. ๐๐ซ๐๐๐๐จ๐๐๐๐๐ฆ๐ฉ – https://lnkd.in/d5Af6_39
Tags:
#DataAnalytics, #DataEngineering, #DataScience, #DataVisualization,

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