Scalable and efficient data pipelines are as important for the success of analytics, data science, and machine learning as reliable supply lines are for winning a war. — Updated paywall-free version: Scalable Efficient Big Data Pipeline Architecture For deploying big-data analytics, data science, and machine learning (ML) applications in the real world, analytics-tuning and model-training is only around 25% of the work. Approximately 50% of the effort goes into making data ready for analytics and ML. The remaining…