What are major modeling issues?

Major modeling issues include data quality, which can lead to inaccurate predictions if the data is incomplete or biased; overfitting, where a model performs well on training data but poorly on unseen data; and interpretability, as complex models may make it difficult to understand underlying mechanisms. Additionally, scalability can be a challenge when models are applied to large datasets or real-time applications. Lastly, assumptions made during modeling can limit applicability and lead to erroneous conclusions if they do not hold true in practice.