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**Data Science**:
- **Scope**: Broad field.
- **Focus**: Predictive models and new insights.
- **Techniques**: Machine learning, advanced stats.
- **Tools**: Python, R, TensorFlow.
- **Outcome**: Future predictions.
**Data Analytics**:
- **Scope**: Narrower focus.
- **Focus**: Understanding past data.
- **Techniques**: Descriptive stats, basic ML.
- **Tools**: Excel, Tableau.
- **Outcome**: Current insights.
In short, data science predicts the future using advanced tools, while data analytics analyzes past data for current insights.
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Data science is an umbrella term for a group of fields that are used to mine large datasets.
Data analytics software is a more focused version of this and can even be considered part of the larger process.
Analytics is devoted to realizing actionable insights that can be applied immediately based on existing queries.
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