Kaggle Vs Enterprise Machine Learning Adoption - Two sides of coin

Reposting Summary from Quora Answer with my perspective added

What you don't learn in Kaggle Competitions

• Determining business problem to solve with data
• Real world data imbalance, Accuracy issues, Maintaining Models
• Miss the challenges of data engineering (What features to select, causational vs correlation in domain context) 

What you learn by experimenting real world data science applications in Production

• Identifying / Reusing Existing data for first level models 
• Identifying pipelines to build for more relevant variables
• ETL / Data Consolidation / Aggregation, Eliminating outliers / Redundant Data

Today's systems have enough Transactional Reporting  / BI Reports in place. The challenge is evolving from the current system, leveraging current data, build a basic model, slowly build pipelines and extend other machine learning use cases.

Happy Learning!!!