Sponsored Post.
“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. The book by Rajesh Jugulum 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 artificial intelligence and machine learning approaches Reviews a structured approach for analytics execution
From Amazon
From CRC Press
For more information visit: rajeshjugulum.com
Quotes:
“This book is an important step in the extension of quality and process improvement concepts to the fields of data & analytics.”
– Prof. Thomas H. Davenport, Author Of Process Innovation, Competing On Analytics, And Only Humans Need Apply
“In an era of Big Data and analytics, an enormous gap remains between business investment and results. How can it be that we are data rich but wisdom poor? Rajesh’s Robust Quality delivers a roadmap for success to any firm that aspires to extract value from its data assets.”
– Randy Bean, Founder and CEO, Newvantage Partners
“In this thought-provoking book, Rajesh brings together data management & analytics with quality & process improvement methods. This capability should be at the core of any successful data-driven organization, and his book provides clear steps on how to get there.”
– Leandro Dallemule, Chief Data Officer, Aig General Insurance
“Dr. Jugulum’s new book, Robust Quality is a missing link to bring a “Deming mindset” to Data Analytics practice. Through this, one can accelerate the quality of decision making process.”
– Dr. Phil Samuel, Chief Innovation Officer, Lean Methods Group
“The book is very innovative and interesting! It allows the reader to deepen the world of analytics to understand how to contextualize it within DMAIC models.”
– Prof. Gabriele Arcidiacono, Head Dept. of Innovation & Information Engineering, G. Marconi University, Italy