Prescriptive Analytics
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- Prescriptive Analytics | SAS
- Prescriptive Analytics | IBM
- Prescriptive Analytics | StitchData
- Prescriptive Analytics | Spiceworks
- Prescriptive Analytics | Forbes
- Advanced AI: from predictive to prescriptive analytics | Wizata
- A Look at Prescriptive Analytics and The Value They Can Deliver | A Look at Prescriptive Analytics and The Value They Can Deliver - CMSwire
- What Is Prescriptive Analytics? How It Works and Examples | Troy Segal - Investopedia
Prescriptive analytics is a type of analytics that uses machine learning and other AI techniques to recommend actions that optimize a specific business objective. AI can support prescriptive analytics in several ways:
- Data analysis: analyze large amounts of data to identify patterns and relationships that are not immediately apparent to humans. This analysis can help identify the key drivers of a particular business outcome and inform the development of prescriptive models.
- Predictive modeling: develop predictive models that forecast future outcomes based on historical data. These models can be used to identify the most likely outcomes of different actions and inform prescriptive recommendations.
- Optimization: optimize complex systems that have many interdependent variables. This optimization can help identify the best course of action to achieve a specific business objective.
- Real-time decision-making: make real-time decisions based on changing conditions. This can help organizations respond quickly to changing circumstances and make decisions that are more likely to achieve their desired outcome.
An AI guides you to the best outcome.
