Historically, the term quality was used to measure performance in the context of products, processes and systems. With rapid growth in data and its usage, data quality is becoming quite important. It is important to connect these two aspects of quality to ensure better performance. This book provides a strong connection between the concepts in data science and process engineering that is necessary to ensure better quality levels and takes you through a systematic approach to measure holistic quality with several case studies. Features: Integrates data science, analytics and process engineering conceptsDiscusses how to create value by considering data, analytics and processesExamines metrics management technique that will help evaluate performance levels of processes, systems and models, including AI and machine learning approachesReviews a structured approach for analytics execution | Robust Quality by Rajesh Jugulum, Hardcover | Indigo Chapters