Difference between revisions of "Prescriptive Analytics"
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* [https://www.spiceworks.com/marketing/ai-in-marketing/articles/prescriptiveanalyticsvs-artificial-intelligence/amp/ Prescriptive Analytics | Spiceworks] | * [https://www.spiceworks.com/marketing/ai-in-marketing/articles/prescriptiveanalyticsvs-artificial-intelligence/amp/ Prescriptive Analytics | Spiceworks] | ||
* [https://www.forbes.com/sites/forbestechcouncil/2021/02/11/predictive-and-prescriptive-analytics-represent-the-future-of-aiits-up-to-us-to-use-them-wisely/?sh=24ac8c965a5d Prescriptive Analytics | Forbes] | * [https://www.forbes.com/sites/forbestechcouncil/2021/02/11/predictive-and-prescriptive-analytics-represent-the-future-of-aiits-up-to-us-to-use-them-wisely/?sh=24ac8c965a5d Prescriptive Analytics | Forbes] | ||
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* [https://www.cmswire.com/customer-experience/a-look-at-prescriptive-analytics-and-the-value-they-can-deliver/ A Look at Prescriptive Analytics and The Value They Can Deliver | A Look at Prescriptive Analytics and The Value They Can Deliver - CMSwire] | * [https://www.cmswire.com/customer-experience/a-look-at-prescriptive-analytics-and-the-value-they-can-deliver/ A Look at Prescriptive Analytics and The Value They Can Deliver | A Look at Prescriptive Analytics and The Value They Can Deliver - CMSwire] | ||
* [https://www.investopedia.com/terms/p/prescriptive-analytics.asp What Is Prescriptive Analytics? How It Works and Examples | Troy Segal - Investopedia] | * [https://www.investopedia.com/terms/p/prescriptive-analytics.asp What Is Prescriptive Analytics? How It Works and Examples | Troy Segal - Investopedia] | ||
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| − | Prescriptive analytics is an advanced form of analytics that uses machine learning and artificial intelligence to recommend actions that optimize a specific business objective. Unlike | + | Prescriptive analytics is an advanced form of analytics that uses machine learning and artificial intelligence to recommend actions that optimize a specific business objective. Unlike [[Predictive Analytics]], which only predicts future outcomes based on historical data, prescriptive analytics goes a step further by identifying the best course of action to achieve the defined objective(s). AI can support prescriptive analytics by analyzing large amounts of data to identify patterns and relationships that are not immediately apparent to humans, developing predictive models that forecast future outcomes based on historical data, optimizing complex systems that have many interdependent variables, and making real-time decisions based on changing conditions. Prescriptive analytics employs AI, ML, and advanced algorithms to specify the desired outcome(s) and optimize the right sequence of actions to achieve it. The AI can explore new lines of thought to propose unseen solutions that are out of reach of the human mind. Using machine learning, AI determines by itself the rules that best suit the data to reach the predefined objective. Prescriptive analytics can help organizations make decisions based on highly analyzed facts rather than jump to under-informed conclusions based on instinct. It can help prevent fraud, limit risk, increase efficiency, meet business goals, and create more loyal customers. When used effectively, it can help organizations make decisions based on highly analyzed facts rather than jump to under-informed conclusions based on instinct. AI can support prescriptive analytics in several ways: |
* <b>Data analysis</b>: 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. | * <b>Data analysis</b>: 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. | ||
Revision as of 13:53, 10 July 2023
YouTube ... Quora ...Google search ...Google News ...Bing News
- Prescriptive & Predictive Analytics ... Predictive Maintenance ... Forecasting ... Market Trading ... Sports Prediction ... Marketing ... Politics ... Excel
- Strategy & Tactics ... Project Management ... Best Practices ... Checklists ... Project Check-in ... Evaluation ... Measures
- Analytics ... Visualization ... Graphical Tools ... Diagrams & Business Analysis ... Requirements ... Loop ... Bayes ... Network Pattern\
- Prescriptive Analytics | SAS
- Prescriptive Analytics | IBM
- Prescriptive Analytics | StitchData
- Prescriptive Analytics | Spiceworks
- Prescriptive Analytics | Forbes
- 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
You are guided by AI to the best possible outcome.
Prescriptive analytics is an advanced form of analytics that uses machine learning and artificial intelligence to recommend actions that optimize a specific business objective. Unlike Predictive Analytics, which only predicts future outcomes based on historical data, prescriptive analytics goes a step further by identifying the best course of action to achieve the defined objective(s). AI can support prescriptive analytics by analyzing large amounts of data to identify patterns and relationships that are not immediately apparent to humans, developing predictive models that forecast future outcomes based on historical data, optimizing complex systems that have many interdependent variables, and making real-time decisions based on changing conditions. Prescriptive analytics employs AI, ML, and advanced algorithms to specify the desired outcome(s) and optimize the right sequence of actions to achieve it. The AI can explore new lines of thought to propose unseen solutions that are out of reach of the human mind. Using machine learning, AI determines by itself the rules that best suit the data to reach the predefined objective. Prescriptive analytics can help organizations make decisions based on highly analyzed facts rather than jump to under-informed conclusions based on instinct. It can help prevent fraud, limit risk, increase efficiency, meet business goals, and create more loyal customers. When used effectively, it can help organizations make decisions based on highly analyzed facts rather than jump to under-informed conclusions based on instinct. 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.
