Artículo: AMZ-B07H34VZF3

Robust Quality: Powerful Integration of Data Science and Process Engineering (Continuous Improvement Series)

Format:

Kindle

Hardcover

Kindle

Paperback

Detalles del producto
Disponibilidad
Sin stock
Peso con empaque
0.84 kg
Devolución
No
Condición
Nuevo
Producto de
Amazon
Viaja desde
USA

Sobre este producto
  • 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 concepts Discusses how to create value by considering data, analytics and processes Examines metrics management technique that will help evaluate performance levels of processes, systems and models, including AI and machine learning approaches Reviews a structured approach for analytics execution

Sin stock

Seleccione otra opción o busque otro producto.

Este producto viaja de USA a tus manos en

Conoce más detalles

Highlight, take notes, and search in the book In this edition, page numbers are just like the physical edition