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what is data science?


🔍 Key Components of Data Science:

  1. Data Collection – Gathering raw data from various sources (e.g., databases, web, sensors).
  2. Data Cleaning – Removing errors, inconsistencies, and missing values.
  3. Exploratory Data Analysis (EDA) – Understanding patterns, trends, and anomalies through statistics and visualization.
  4. Model Building – Using machine learning algorithms to make predictions or find hidden structures.
  5. Model Evaluation – Testing the model's performance and adjusting for better accuracy.
  6. Deployment – Making the model available in real-world applications (e.g., web apps, APIs).
  7. Communication – Translating technical findings into business decisions using reports, dashboards, or presentations.

💡 Example:

A retailer uses data science to:

  • Predict which products will sell best next season.
  • Optimize pricing strategies.
  • Segment customers for targeted marketing.

In simple terms: Data Science = Data + Algorithms + Business Insight

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