Is The Pace Of AI Development Slowing Down?
Got Data Science Platform, Visualization, and MLOps Tools, yet struggling with scaling AI? Feature Engineering holds the key to faster development! Data science, analytics, and BI leaders in disparate industries such as financial services, retail, and manufacturing have been spending heavily on AI tools, upgrading data infrastructure, augmenting BI with ML. Your organization may already have an AI Center of Excellence (CoE) to support LoB’s where the teams are building predictive applications that can predict churn, detect fraud, and forecast inventory. Yet, for the vast majority of enterprise customers, the AI development has been slow, AI initiatives have not scaled according to expectations. What can you do to scale AI development, accelerate adoption and propel innovation? You need to step back, analyze the data science process and focus on three core buckets in the development workflow - Data Preparation, Feature Engineering, and Machine Learning. More specifically, answer three critical questions: Who…
