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Predictive analytics are a part of advanced analytics that provide a probable picture of what might happen in the future. Considering the previous behaviors from the descriptive analytics, predictive analytics might help in setting the real-time goals in an effort to optimize planning within an organization.
Predictive analytics capture the likelihood of a future outcome using different statistical techniques including, machine learning, root-cause analysis, predictive modeling, artificial intelligence, data mining and other forms of analysis based upon predictive models.
Predictive analytics identify future trends and patterns, and they provide insights about what may come in the future. When a company forecasts future outcomes and plans accordingly, then there is a far higher probability that it will be able to measurably improve the operations throughout the various internal structures of the organization.
Real World Examples:
Predictive analytics can be very complex and require a much deeper understanding than traditional descriptive analytics. The majority of predictive analytics are conducted by data scientists, business analysts, and statisticians. The success or failure of an organization heavily depends on proper future analysis.
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