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Prescriptive Analytics

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Prescriptive Analytics

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Âge recommandé: 16 ans
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Prescriptive Analytics Version en ligne

Prescriptive Analytics

par Ray Larkin
1

modelling recommendations algorithms more optimize complex learning future new right different prescriptive

The relatively field of analytics allows users to " prescribe " a number of possible actions and guide them towards a solution . In a nutshell , these analytics are all about providing advice . Prescriptive analytics attempts to quantify the effect of decisions in order to advise on possible outcomes before the decisions are actually made . At their best , prescriptive analytics predicts not only what will happen , but also why it will happen , providing regarding actions that will take advantage of the predictions .
These analytics may recommend one or possible courses of action . Essentially they predict multiple futures and allow companies to assess a number of possible outcomes based upon their actions . Prescriptive analytics use a combination of techniques and tools such as business rules , , machine and computational procedures . These techniques are applied against input from many different data sets including historical and transactional data , real - time data feeds , and big data .
Prescriptive analytics are relatively to administer , and most companies are not yet using them in their daily course of business . When implemented correctly , they can have a large impact on how businesses make decisions , and on the company's profitability . Larger companies are successfully using prescriptive analytics to production , scheduling and inventory in the supply chain to make sure that are delivering the right products at the time and optimizing the customer experience .

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