Limitations of predictive analytics

 Limitations of predictive analytics  

One of the most significant limitations of predictive analytics is data quality . Predictive models rely on large, accurate, and relevant datasets to produce accurate predictions. If the data used to train the model is incomplete, inaccurate, or biased, the model's predictions will also be flawed. 

While predictive analytics might seem like the ideal inclusion for application teams, it's worth noting the risks. These include  data privacy and security concerns, model accuracy and bias challenges, users perception and trust issues and the dependency of data quality and availability.