Common Data Sense for Professionals
A Process-Oriented Approach for Data-Science Projects
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Leveringstid: Sendes innen 21 dager
Leveringstid: Sendes innen 21 dager
The jump from personal data usage for self-betterment to mass data analysis for business process improvement often feels bigger to us than it is. In turn, we often think big data analysis requires tools held only by advanced degree holders. Although advanced degrees are certainly valuable, this book illustrates how it is not a requirement to adequately run a data science project. Because we are all already data users, with some simple strategies and exposure to basic analytical software programs, anyone who has the proper tools and determination can solve data science problems. The process presented in this book will help empower individuals to work on and solve data-related challenges.
The goal of this book is to provide a step-by-step guide to the data science process so that you can feel confident in leading your own data science project. To aid with clarity and understanding, the author presents a fictional restaurant chain to use as a case study, illustrating how the various topics discussed can be applied. Essentially, this book helps traditional businesspeople solve data-related problems on their own without any hesitation or fear. The powerful methods are presented in the form of conversations, examples, and case studies. The conversational style is engaging and provides clarity.
Forlag: CRC Press
Format: 23 x 15 cm
Rajesh takes a fresh approach to describing the importance of data and data-based thinking. I think it is unique and most helpful that he is able to simplify the topic of data science. Once simplified we are all able to think about the importance of using data more clearly to solve problems.
-- Don Callahan, Executive Chairman, TIME
Jugulum’s book addresses two important trends in data science: adopting a process approach, and democratizing the process. Appropriate for the topic, it addresses the issues in an accessible, conversational fashion. It’s a rare book that is both easy and important to read.
--Thomas H. Davenport, Distinguished Professor, Babson College and Visiting Professor, Oxford Saïd Business School, Fellow, MIT Initiative on the Digital Economy, Author of Competing on Analytics and The AI Advantage
While it lacks the hype of "Machine Learning" and "Artificial Intelligence"; understanding the potential for Data Science to extract insights from structured and unstructured data is critical to virtually every skilled occupation, and to every investor. By adopting a conversational approach, Rajesh introduces data science in an informal yet informative manner and brings the field comfortably within reach of readers without an engineering, maths, or computer science background.
-- Gareth Genner, CEO and Group General Counsel, Trust Stamp
A fresh approach to data science, making the concepts clear through an informal conversational style. This book simplifies this critical approach in business and makes it understandable to the layperson, even without a mathematical background.-- Desh Deshpande, Entrepreneur, Life member MIT Corporation
I don't know how many times in my career I have heard "if I could only do what the big corporations do and apply that to my small business I could really grow". Rajesh has done that here. He has taken data science down to a level that anyone can use it. He has helped eliminate the "If I could only".
-Sandra Harry, Chairman of the Board, Dr. Mikel J Harry Six Sigma Management Institute Inc., Chief Executive Officer, The Great Discovery, LLC
Dr. Jugulum brings deep knowledge of data science and analytics to anyone interested in understanding the "why" and "how" of data analytics. "Common Data Sense for Professionals" shows through example how data science should be approached and why it is necessary to solve common business problems in today’s economic climate. Those who do not understand and practice data analytics are doomed to business failure in our increasingly connected world. Dr. Jugulum clearly shows us the path to success regardless of the type of business we are conducting. This book should be required reading for all business operators, both large and small.
-- Julianna Lindsey MD MBA, CEO/CMO, Radiant Precision Medicine
Rajesh outlines a clear process approach to analyze data and make results available. Once data scientists and "non data scientists" alike understand the results, a conversation leading actionable decisions can be made. Great read.
-- Mark Prince, MD MBA, Director of Inpatient Gastroenterology, GI Hospital Group
Data science and analytics can be an overwhelming and complex topic to many readers, yet, in his book, Rajesh is able to break this down into very digestible concepts. The book follows the interaction and conversation between the two main characters, all the while delivering a foundational approach to data analysis and problem solving. A fast, enjoyable read, this book really helps to shed light on how easy it is to apply data science to solving everyday problems.
-- Dan Duzan, MD, Board Certified Internist/Hospitals
Data science has made great strides in helping businesses solve important problems. But still, too often business people and data scientists have a hard time working together because they come from two very different worlds. The fanciful perception of data science and AI as "magic wands" which can be waved at problems to solve them hasn’t helped. In Common Data Sense for Professionals, Rajesh Jugulum has de-mystified data science for non-technical people. His focus on problem solving with sound process management practices places data science in its proper place…as a vast and useful toolkit that, properly used, can work wonders.
-- Heather H. Wilson, CEO, CLARA Analytics
Now more than ever, we need to be guided by data, science, and facts to make informed decisions. In his new book, Common Data Sense for Professionals, Rajesh Jugulum seeks to demystify the world of data science for the layperson. As Thomas Redman notes in the Foreword to the book, "Slowly perhaps, but inexorably, data are invading every aspect of our personal, public, and business lives.". This book represents a helpful step forward for those seeking to understand the role of data science in the world today."
– Randy Bean, Author of Fail Fast, Learn Fast: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI, Founder and CEO, NewVantage Partners LLC
In this book, Rajesh finds a very systematic way to understand the problem at hand, methodically steps through relevant data collection and structured way to solve the problem He uses conversational method to introduce complex concepts that makes it easy to understand. A must read for anyone who wants to understand data science.
-- Gyan Dwibedy, Chief Data and Analytics Officer, Molina Healthcare
Rajesh Jugulum has produced a jem! In the Overview, he states: "The goal of this book is to help regular people feel at ease, in order for them to use data-based thinking and solve data-related problems." He has thoroughly succeeded! Through the use of a hypothetical, conversational case study, much in the vein of The Goal, Jugulum demonstrates that data science is not limited to "specialists" with advanced degrees, but is rather a way of thinking that is needed by everyone. I particularly applaud his emphasis on carefully understanding the problem one is trying to solve, before jumping into analysis; a critical point often overlooked in the technical literature. Highly recommended.
-- Roger Hoerl, Brate-Peschel Associate Professor of Statistics, Union College
In his book, Rajesh Jugulum walks the readers through "analytic thinking" required for generating insights for informed decision making. Through a systematic approach that includes formulating problems, structuring data collection, and analyzing relevant data, he shows how one can easily solve data science problems. Addressing the topics in the form of a conversation between a mentor and a mentee engages readers. It is a must-read for anyone interested in becoming a data scientist.
-- Raj Echambadi, President, Illinois Institute of Technology
Data has become one of the most valuable resources we have in the Information Age. Until now, the ability to extract the real value contained within this resource has been limited to a rare group of data scientists and Ph.Ds. In Common Data Sense for Professionals, Jugulum demystifies the effective analysis of data in a way that democratizes it making it possible for a wide range of roles and personas to make informed business decisions.
- Charlie Guyer, Founder, Guyer Group,
I was delighted by how clearly Rajesh demystifies the practice of data science and dismantles the misconceived notion that all data science must be difficult or complex. The casual, conversational narrative quickly held my attention while providing a stage for exploring real world applications. As a data science practitioner, I use data in every aspect of my professional life to solve business problems. After reading Common Data Sense for Professionals, I'm reminded that not every problem we, as individuals, face is business related. With the vast access individuals have to data recording devices in the present day, or even plain paper and pencil, the process Rajesh outlines can be applied just as easily at home to improve every aspect of our lives where a problem can be found.
-- Christopher Heien, Senior Data Scientist, Evernorth
Solving problems and answering questions through analysis is typical procedure in data science. Data science involves experimenting by constructing models to predict outcomes or discover new information. Do you want to explore the realm of the latest developments in the data world? Are you considering a career in which data science is significant? Do you want to expand your knowledge? Whatever your purpose, in his book "Common Data Sense for Professionals -Process Oriented Approach for Data Science Projects", Rajesh Jugulum has given us an interactive simple discourse to help non-technical consumers comprehend the use of data in overcoming real life challenges.
-- Ahmed Ankit, Dean – School of Business and Quality Management, HBMSU, Dubai»
Chapter 1: The Meeting of Manju and Jim
Chapter 2: Understanding the Problem
Chapter 3: Analyzing the Problem and Collecting Data
Chapter 4: Creating and Analyzing Models
Chapter 5: Project Structure
Chapter 6: Data Science Stories and Case Example Analysis
Chapter 7: Concept Review
Chapter 8: Manju and Jim's Concluding Meeting
process engineering and data science at Cigna, Citi Group and Bank of America. Rajesh completed his PhD under the guidance of Dr. Genichi Taguchi. Before joining the financial industry, Rajesh was at Massachusetts Institute of Technology (MIT)
where he was involved in research and teaching.
Currently, Rajesh is Co-founder and Chief Data Science & Analytics Officer at dataDragon, a cloud based data science/analytics firm. He also teaches at Northeastern University, Boston as an affiliate professor. He is also an affiliate graduate faculty at University of Arkansas, Little Rock.
Rajesh is the author/co-author of several papers and five books including books on robust quality, data quality and design for lean six sigma. Rajesh also holds two US patents. Rajesh is a Fellow of American Society for Quality (ASQ) and also a Fellow
of Royal Statistical Society (RSS) and his other honors include ASQ’s Feigenbaum Medal, International Technology Institute’s Rockwell Medal and 2012 Recognition Award from Industrial and Systems Engineering Department of Wayne State University. He has been listed in the “Who’s Who in the World” list by Marquis Who's Who publication board. He was featured as “Face of Quality” in the September, 2001 issue of Quality Progress magazine and his Profile was also published in the October 2002 issue of the Journal of Quality Engineering Society.
Rajesh has delivered talks as the keynote speaker at several conferences, symposiums, and events related to data science, analytics and process engineering. He has also delivered lectures at several universities/companies across the globe
and participated as a judge in data-related competitions.