It's All Analytics!
CRC Press (Verlag)
978-0-367-35968-3 (ISBN)
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.
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.
Foreword Number One. Foreword Number Two. Foreword Number Three. Preface. Endorsements. Authors. Chapter 1. You Need This Book. Chapter 2. Building a Successful Program. Chapter 3. Some Fundamentals – Process, Data, and Models. Chapter 4. It's All Analytics! Chapter 5. What Are Business Intelligence (BI) and Visual BI? Chapter 6. What Are Machine Learning and Data Mining? Chapter 7. AI (Artificial Intelligence) and How It Differs from Machine Learning. Chapter 8. What Is Data Science? Chapter 9. Big Data and Bigger Data, Little Data, Cloud, and Other Data. Chapter 10. Statistics, Causation, and Prescriptive Analytics. Chapter 11. Other Disciplines to Dive in Deeper: Computer Science, Management/Decision Science, Operations Research, Engineering (and More). Chapter 12. Looking Ahead. Index.
| Erscheinungsdatum | 10.07.2020 |
|---|---|
| Zusatzinfo | 1 Tables, black and white; 20 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 178 x 254 mm |
| Gewicht | 703 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Mathematik / Informatik ► Informatik ► Netzwerke | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Medizin / Pharmazie ► Gesundheitswesen | |
| Wirtschaft ► Betriebswirtschaft / Management ► Unternehmensführung / Management | |
| ISBN-10 | 0-367-35968-5 / 0367359685 |
| ISBN-13 | 978-0-367-35968-3 / 9780367359683 |
| Zustand | Neuware |
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