Leila Halawi, Amal Clarke, Kelly George

Harnessing the Power of Analytics (eBook, PDF)

• Format: PDF

Produktbeschreibung

This text highlights the difference between analytics and data science, using predictive analytic techniques to analyze different historical data, including aviation data and concrete data, interpreting the predictive models, and highlighting the steps to deploy the models and the steps ahead. The book combines the conceptual perspective and a hands-on approach to predictive analytics using SAS VIYA, an analytic and data management platform. The authors use SAS VIYA to focus on analytics to solve problems, highlight how analytics is applied in the airline and business environment, and compare several different modeling techniques. They decipher complex algorithms to demonstrate how they can be applied and explained within improving decisions.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 150
• Erscheinungstermin: 31. Januar 2022
• Englisch
• ISBN-13: 9783030897123
• Artikelnr.: 63376322

Autorenporträt

Dr. Leila Halawi is a tenured associate professor in the Graduate studies department of the College of Aeronautics, Worldwide Campus. She is the program chair for the Master of Aviation sustainability and associate program chair for the master of I.T. Entrepreneurship. Previously, Dr. Halawi served as the MIS Discipline Chair, Chair of the Research Committee for the Senate, and the Director of Research for the College of Business. She developed many of the courses within the MMIS program. She holds a Certification from Sloan C Consortium in Online Teaching and a certificate from Quality Matters on Applying the Q.M. Rubrics (APPQMR). She is an advisory board member and a reviewer for the Enterprise Architecture Body of Knowledge (EABOK), Mitre Corporation. She is a Reviewer for the Journal of Computer Information Systems (JCIS) and the International Association for computer information systems (IACIS). She is also a program committee member and reviewer for the European Conference on Social Media (ECSM), the European Conference on Knowledge Management (ECKM) and the International Conference on Intellectual Capital and Knowledge Management (ICIKM), the Federated Conference on computer science and information systems (FEDCSIS). She is also part of the I.T. editorial board of the multimedia educational resource for learning and online teaching (MERLOT). She received the SAS 2020 Emerging Educator Award Recipient. Her current book that she co-authored, "Applying Predictive Analytics Finding Value in Data," was published by Springer in June 2019. Her research has been published in the Journal of Computer Information Systems (JCIS), the Learning Organization Journal, the Journal of Business Education, the Electronic Journal of Knowledge Management (EJKM), the Academy of Information and Management Sciences Journal (AIMSJ), Journal of International Technology and Information Management, Journal of Education for Business, Academy of Healthcare Management Journal (AHCMJ) among others. She is frequently invited to present her research at national and international conferences. Her current research interests include knowledge management, Business Intelligence, information systems success and strategy, and ethical impacts of information technology, promoting innovation, curriculum development, design, enterprise architecture and systems, big data, and predictive analytics.

Dr. Amal Clarke is a lecturer at the London School of Economics and Political Science (LES) and an adjunct professor in the Department of Arts and Sciences at ERAU. She has been a Mathematics teacher and coordinator for decades at many levels, from pre-calculus and calculus courses to graduate courses. She has been a private Maths tutor from elementary up to postgraduate level. Her success in teaching has been recognized with several awards, one of which was awarded first prize by Microsoft in 2007. Maths experts from twenty-five countries participated in this competition: applying mathematics in real life. She got a degree in computer science with an honors GPA while being a full-time teacher, private tutor, and two kids' mother. She got a Masters Diploma in Mathematics with distinction and a Ph.D. in Pure Maths from the Birkbeck University of London. Dr Clarke published papers in Communications in Algebra and other journals.

Dr Clarke has constantly been learning and gaining experience as to what makes an effective practitioner of the craft, improving and focusing on her skills. Together with a commitment to continue learning and adjusting, she brings this experience to her passion and love for Mathematics. Amal is eager to implement her decades of experience as a student and Mathematics lecturer by building bridges between Mathematics, Statistics, and real-life problems.

Dr. Whealan George serves as an associate professor in the Social Sciences and Economics Program in the Department of Arts and Sciences at ERAU. Dr. Whealan George currently teaches Economics and Statistics courses for ERAU. Dr. Whealan George has over twenty-eight years of teaching experience. Dr. Whealan George started teaching as a favor to a colleague. When the U.S. Navy invaded her family life and required her to move to China Lake, California, she discovered ERAU and continued to teach. Dr. Whealan George graduated with a BBA in Finance from Southern Methodist University. She worked as a Banking Officer at Bank of American (formerly NCNB Texas) for two years. While completing her Masters in Economics at Southern Methodist University, she began work as an economist at the Federal Reserve Bank in Dallas. Her research areas include aviation economics, sustainable aviation, international trade, corporate banking finance, aviation, agriculture, petroleum and services industries, national income distribution, and educational economics.

Inhaltsangabe

Chapter 1. Introduction to Analytics and Data Science.- Chapter 2. Data Types Structure & Data Preparation Process.- Chapter 3. Data Exploration and Data Visualization. Chapter 4. Evaluating Predictive Performance.- Chapter 5. Decision Trees & Ensemble.- Chapter 6. Regression Models.- Chapter 7. Neural Networks.- Chapter 8. Model Deployment.