Overview

"It's All Analytics! The Foundations of AI, Big Data and Data Science Landscape for Professionals in Healthcare, Business, and Government (978-0-367-35968-3, 325690) Professionals are challenged each day by a changing landscape of technology and terminology. In recent history, especially in the last 25 years, there has been an explosion of terms and methods that automate and improve decision-making and operations. One term, ""analytics,"" is an overarching description of a compilation of methodologies. But AI (artificial intelligence), statistics, decision science, and optimization, which have been around for decades, have resurged. Also, things like business intelligence, online analytical processing (OLAP) and many, many more have been born or reborn. How is someone to make sense of all this methodology and terminology? This book, the first in a series of three, provides a look at the foundations of artificial intelligence and analytics and why readers need an unbiased understanding of the subject. The authors include the basics such as algorithms, mental concepts, models, and paradigms in addition to the benefits of machine learning. The book also includes a chapter on data and the various forms of data. The authors wrap up this book with a look at the next frontiers such as applications and designing your environment for success, which segue into the topics of the next two books in the series."

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9780367359683

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Reviews

Burk and Miner have created a map to guide anxious and overwhelmed executives to the rapidly changing and often unwieldy landscape of data and analytics techniques and technologies. Their survey cuts through the hype and hyperbole and enables data practitioners and non-practitioners to clearly communicate how to understand, optimize, and ultimately transform their business processes through analytics. Highly recommended. Josh Wills, Former Director of Data Engineering, Slack It's All Analytics! deserves a prominent place on executives' bookshelves. Burk and Miner have undertaken a noteworthy challenge in their synthesis of data science, machine learning, data mining, artificial intelligence and statistics, presented at a level both useful and provocative to business leaders. The chapter on statistics particularly fills a gap in current discourse about the latest fashions in AI and Machine Learning. Loren Williams, Former Chief Data Scientist, Big Four Almost every company in the world now understands the critical importance of collecting, processing, analyzing, and acting upon data. The largest hurdles impeding companies in this process aren't caused by technical limitations or a lack of trained specialists, but by the people who need to understand how it affects them, what can be done, and how to implement and manage it within their organization, but don't. In this book, Burk and Miner help to solve that problem in language that is straightforward, sensible, and based on their considerable experience. If actionable analytics is a key need for your organization, and you want to minimize the struggle and confusion required to implement it, you should read this book. Dylan Zwick, Former Director of Data Science at Overstock.com

The applications of computational methods in machine learning and artificial intelligence are rapidly changing the world that we work and live in. Many traditional industries and professions are being fundamentally reimagined as AI industries. It is becoming imperative for those at every level in companies and organizations (not to mention the general public) to understand both what will AI do FOR me? and what will AI do TO me? . The rapid acceleration in the development and deployment of these technologies is creating an increasing gap in understanding. Many who need to know don't even know what they don't know. This, coupled with hyperbolic news releases on some new AI application-of-the-moment, leaves the nontechnical observer with no easy solution to bridging this gap. Fortunately, Scott Burk and Gary Miner have astutely recognized this gap in understanding and offer a starting point for bridging this gap in It's All Analytics! This volume provides a 20,000-foot overview of these technologies and serves as an easily grasped read for beginning the journey to deeper understanding or broadening one's knowledge base. While it is geared towards those with little or no understanding of AI and machine learning, it is a valuable resource for those working in these areas who may have a siloed view of the fields. The authors are uniquely qualified to deliver this overview as they are both not only industry practitioners of these technologies, but also educators skilled at making these topics accessible to the neophyte. They have obviously paid great attention to readability and organized the material in a way that provides a memorable framework for pinning the reader's newly gathered knowledge. Additionally, the book is richly referenced with additional resources for taking a deeper dive into specific subject matter. I'd like to be among the first to congratulate the authors on this timely, engaging, useful, and highly informative read. John W. Cromwell, M.D., FACS, FASCRS Associate Chief Medical Officer | Director of Surgical Quality and Safety University of Iowa Hospitals & Clinics Director, Division of Gastrointestinal, Minimally Invasive, and Bariatric Surgery Clinical Associate Professor University of Iowa Carver College of Medicine Faculty, Interdisciplinary Graduate Program in Informatics University of Iowa Graduate College Iowa City, IA The rise of artificial intelligence brings us excitement and hope, but also causes some anxiety and even fear. The internet is flooded with a sea of terminology and concepts. For anyone who is interested in learning more about AI, numerous online courses, articles, blogs are at fingertips. However, not all information has been curated thus resulted in tremendous amount of confusion and a great deal of misunderstanding. I am thrilled that Scott and Gary compact several decades of history of AI, data science, analytics, an incredible amount of terminology, concepts, and a comprehensive view of the current landscape, all into this one book. With their years of experience across a broad spectrum of industry, the book offers many practical examples and thought exercises, and explains complex concepts in simple language. Business executives will benefit from this book with in-depth understanding of the technical concept and capability, as well as organizational planning and strategy; people leaders will get help to build a strong team with the right talents, tooling, and capability; technical professionals will broaden their view of the data science world and have more clear expectation of career path. I have found this book most comprehensive and practical on the market, and it offers an objective and informed view. What makes it even more valuable is that it is a synthesis book and serves as a reference that can be used for many years to come. If you have an ambition to sail in the sea of AI, this is the compass that you must carry in your pocket. Xingchu Liu, Ph.D. President of BlackLocus The Home Depot Innovation Lab It's All Analytics! by Scott Burk and Gary Miner. There is a lot to like about this book. A whole lot. The first thing I liked was that it was interesting. It doesn't read like a cold, boring academic treatise. Instead it reads almost like a mystery novel - where one page invites the next. This plain-spoken approach opens the doors of analytics to anyone who is interested. And that is good. Because in the world to come, analytics is THE key to success and survival. Explaining analytics to the everyman is not a simple or easy thing to do. For many years analytics has been wrapped up in confusing algorithms, spurious terms, and specious formulae. Yesterday you had to have a phd in order to gain a foothold into the wondrous realm of analytics. But in tomorrow's world analytics are going to become so pervasive that analytics will become as common as soda pop or ice cream. In order to be able to swim with the sharks of tomorrow you have to have the basics of analytics. And the book It's All Analytics! explains concepts and practices in easy to understand terms. This book is for anyone who wishes to be conversant in the language of tomorrow. Bill Inmon, Denver, Colorado Burk and Miner have created a map to guide anxious and overwhelmed executives to the rapidly changing and often unwieldy landscape of data and analytics techniques and technologies. Their survey cuts through the hype and hyperbole and enables data practitioners and non-practitioners to clearly communicate how to understand, optimize, and ultimately transform their business processes through analytics. Highly recommended. Josh Wills Former Director of Data Engineering, Slack It's All Analytics! deserves a prominent place on executives' bookshelves. Burk and Miner have undertaken a noteworthy challenge in their synthesis of data science, machine learning, data mining, artificial intelligence and statistics, presented at a level both useful and provocative to business leaders. The chapter on statistics particularly fills a gap in current discourse about the latest fashions in AI and Machine Learning. Loren Williams Former Chief Data Scientist, Big Four

Author Information

"Scott Burk has been solving complex business and health care problems for twenty-five years through science, statistics, machine learning and business acumen. Scott started his career, well actually in analytics, as as an analytic chemist after graduating with a double major in biology and chemistry from Texas State University. He continued his education, going to school at night taking advanced courses in science and math at the University of Texas at Dallas (UTD). He then started programming at the toxicology lab where he was working and thus started taking computer science (CS) and business courses until he graduated with a Master’s in Business with a concentration in finance soon after from UTD. Texas Instruments (TI) hired him as a financial systems analyst in Semiconductor Group, but due to TI’s needs and Scott’s love of computers, he soon after became a systems analyst for corporate TI. He worked there for three years and started itching to get back to school (even though, he continued to take courses at night (Operations Research and CS) through TI’s generous educational program). TI granted him an educational leave of absence and he went to Baylor University to teach in the business school and get a PhD in statistics. He joined Baylor as a non-tenure track professor teaching Quantitative Business Analysis (today = business analytics). After graduating, Scott went back to TI as a Decision Support Manager for the consumer arm of TI (today = consulting data scientist). Where he engaged in many functional areas – marketing and sales, finance, engineering, logistics, customer relations the call center and more. It was a dream job, but unfortunately, TI exited that business. Scott joined Scott and White, a large integrated healthcare delivery system in Texas as a consulting statistician. He moved into an executive role as Associate Executive Director, Information Systems leading Data Warehousing, Business Intelligence and Quality Organizations working with clinics, hospitals and the health plan. At the same time, he received a faculty appointment and taught informatics with Texas A&M University. He left, but later came back to Baylor, Scott and White (BSW) as Chief Statistician for BSW Healthplan. Scott continued his education, getting an advanced management certification from Southern Methodist University (SMU) and Master’s Degree (MS) in Data Mining (machine learning) from Central Connecticut State University. Scott is a firm believer in life-long learning. He also worked as Chief Statistician at Overstock, re-engineering the way they tested and evaluated marketing campaigns and other programs (analytics, statistics). He launched their ‘total customer value’ program. He was a Lead Pricing Scientist (analytics, optimization) for a B2B pricing optimization company (Zilliant) for a number of years. He thoroughly enjoyed working with a rich diverse, well-educated group that affected the way he looks at multidisciplinary methods of solving problems. He was a Risk Manager for eBay/Paypal identifying fraud and other risks on the platform and payment system. He has been working the last few years supporting software development, marketing and sales, specifically data infrastructure, data science and analytics platforms for Dell and now TIBCO. He supports his desire to learn and keep current by writing and teaching in the Masters of Data Science Program at City University of New York.   Dr. Gary Miner received his B.S. from Hamline University, St. Paul, Minnesota with biology, chemistry and education majors; M.S. in Zoology & Population Genetics from the University of Wyoming, and his Ph.D. in Biochemical Genetics from the University of Kansas as the recipient of a NASA Pre-Doctoral Fellowship. During the doctoral study years, he also studied mammalian genetics at The Jackson Laboratory, Bar Harbor, ME, under a College Training Program on an NIH award; and another College Training Program at the Bermuda Biological Station, St. George’s West, Bermuda in a Marine Developmental Embryology Course, on an NSF award; and a third College Training Program held at the University of California, San Diego at the Molecular Techniques in Developmental Biology Institute, again on an NSF award. Following that he studied as a Post-Doctoral student at the University of Minnesota in Behavioral Genetics, where, along with research in schizophrenia and Alzheimer’s Disease, he learned ""how to write books"" from assisting in editing two book manuscripts of his mentor, Irving Gottesman, Ph.D. (Dr. Gottesman returned the favor 41 years later by writing two tutorials for this PRACTICAL TEXT MINING book). After academic research and teaching positions, Dr. Miner did another two-year NIH-Post-Doctoral in Psychiatric Epidemiology and Biostatistics at the University of Iowa where he became thoroughly immersed in studying affective disorders and Alzheimer’s Disease. All together he spend over 30 years researching and writing papers and books on the genetics of Alzheimer’s Disease (Miner, G.D., Richter, R, Blass, J.P., Valentine, J.L, and Winters-Miner, Linda. FAMILIAL ALZHEIMER’S DISEASE: Molecular Genetics and Clinical Perspectives. Dekker: NYC, 1989; and Miner, G.D., Winters-Miner, Linda, Blass, J.P., Richter, R, and Valentine, J.L. CARING FOR ALZHEIMER’S PATIENTS: A Guide for Family & Healthcare Providers. Plenum Press Insight Books: NYC. 1989). Over the years he held positions, including professor and chairman of a department, at various universities including The University of Kansas, The University of Minnesota, Northwest Nazarene University, Eastern Nazarene University, Southern Nazarene University, Oral Roberts University Medical School where he was Associate Professor of Pharmacology and Director of the Alzheimer Disease & Geriatric Disorders Research Laboratories, and even for a period of time in the 1990’s was a visiting Clinical Professor of Psychology for Geriatrics at the Fuller Graduate School of Psychology & Fuller Theological Seminary in Pasadena, CA. In 1985 he and his wife, Dr. Linda Winters-Miner [author of several tutorials in this book] founded The Familial Alzheimer’s Disease Research Foundation [aka ""The Alzheimer’s Foundation] which became a leading force in organizing both local and international scientific meetings and thus bringing together all the leaders in the field of genetics of AD from several countries, which then lead to the writing of the first scientific book on the genetics of Alzheimer’s Disease; this book included papers by over 100 scientists coming out of the First International Symposium on the Genetics of Alzheimer’s Disease held in Tulsa, OK in October, 1987. During part of this time he was also an Affiliate Research Scientist with the Oklahoma Medical Research Foundation located in Oklahoma City with the University of Oklahoma School of Medicine. Dr. Miner was influential in bringing all of the world’s leading scientists working on Genetics of AD together at just the right time when various laboratories from Harvard to Duke University and University of California-San Diego, to the University of Heidelberg, in Germany, and universities in Belgium, France, England and Perth, Australia were beginning to find ""genes"" which they thought were related to Alzheimer’s Disease. During the 1990’s Dr. Miner was appointed to the Oklahoma Governor’s Task Force on Alzheimer’s Disease, and also Associate Editor for Alzheimer’s Disease for THE JOURNAL OF GERIATRIC PSYCHIATRY & NEUROLOGY, which he still serves on to this day. By 1995 most of these dominantly inherited genes for AD had been discovered, and the one that Dr. Miner had been working on since the mid-1980’s with the University of Washington in Seattle was the last of these initial 5 to be identified, this gene on Chromosome 1 of the human genome. At that time, having met the goal of finding out some of the genetics of AD, Dr. Miner decided to do something different, to find an area of the business world, and since he had been analyzing data for over 30 years, working for StatSoft, Inc. as a Senior Statistician and Data Mining Consultant seemed a perfect ""semi-retirement"" career. Interestingly (as his wife had predicted), he discovered that the ""business world"" was much more fun than the ""academic world"", and at a KDD-Data Mining meeting in 1999 in San Francisco, he decided that he would specialize in ""data mining"". Incidentally, he first met Bob Nisbet there who told him, ""You just have to meet this bright young rising star John Elder!"", and within minutes Bob found John introduced me to him, as he was also at this meeting. As Gary delved into this new ""data mining"" field, and looked at statistics text books in general, he saw the need for ‘practical statistical books’ and started writing chapters, and organizing various outlines for different books. Gary, Bob, and John kept running into each other at KDD meetings, and eventually at a breakfast meeting in Seattle in August of 2005 decided they needed to write a book on data mining, and right there re-organized Gary’s outline which eventually became the book Handbook of Statistical Analysis and Data Mining Applications, 2009, published by Elsevier. And then, in 2012, he was the lead author on a 2nd book from Elsevier/Academic Press, PRACTICAL TEXT MINING. And then a 3rd in this ""series"" in 2015: PRACTICAL PREDICTIVE ANALYTICS and DECISIONING SYSTEMS FOR MEDICINE. All thanks to Dr. Irving Gottesman, Gary’s ""mentor in book writing"", who planted the seed back in 1970 while Gary was doing a post-doctoral with him at the University of Minnesota. His latest book was released in 2018, the 2nd Edition of the 2009 book HANDBOOK OF STATISTICAL ANALYSIS and DATA MINING APPLICATIONS (https://www.amazon.com/Handbook-Statistical-Analysis-Mining-Applications/dp/0124166326/); and a 2019 book written more for the layperson and decision maker, titled: HEALTHCARE’S OUT SICK – PREDIDCTING A CURE – SOLUTIONS THAT WORK!!! Published by Routledge / Taylor and Francis Group – ""A Productivity Press Book"" (https://www.amazon.com/HEALTHCAREs-OUT-SICK-PREDICTING-INNOVATIONS/dp/1138581097). Dr. Miner is currently working on a 2nd and 3rd book in a series with Scott Burk, Ph.D., and also teaches courses periodically in ""Predictive Analytics and Healthcare Analytics"" for the University of California-Irvine."

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