Unlocking Potential Through Data Standardization

Organizations can unlock significant opportunities by first standardizing their data, allowing for advanced analyses like forecasting and sentiment analysis. However, building an internal machine learning (ML) team presents challenges, particularly in hiring, as traditional software engineers may not possess the specific skills to assess ML candidates. The distinction between software engineering and machine learning requires different evaluation metrics, creating a communication gap that complicates the hiring process for ML teams.