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Business Intelligence, Analytics, Data Science, and AI, Global Edition de Dursun Delen

Business Intelligence, Analytics, Data Science, and AI, Global Edition

Autor Dursun Delen, Efraim Turban, Ramesh Sharda
en Limba Engleză Paperback – 17 iun 2024

Codul sursă și resursele practice constituie nucleul acestui volum, oferind cititorului exerciții de tip hands-on ce pot fi rulate pe diverse platforme software pentru a simula scenarii reale de business. Observăm o consolidare strategică a conținutului, Pearson Education fuzionând în această ediție globală două titluri de referință pentru a crea un ghid exhaustiv despre impactul inteligenței artificiale în management.

Structura este riguros organizată pe pilonii fundamentali ai analizei de date. Ne-a atras atenția progresia logică de la Descriptive Analytics — unde se pune accent pe natura datelor și vizualizare — către Predictive Analytics, explorând algoritmi de data mining și analiza textului. Volumul culminează cu secțiuni avansate de Deep Learning și Prescriptive Analytics, oferind soluții de optimizare și simulare. Cititorul care a aplicat ideile din Analytics, Data Science, & Artificial Intelligence de Efraim Turban va găsi aici o actualizare esențială, completată cu patru capitole noi ce analizează tehnologii emergente precum ChatGPT și peisajul actual al instrumentelor AI.

Spre deosebire de Business Analytics with R and Python, care se concentrează pe limbaje specifice de programare, această lucrare semnată de Dursun Delen, Efraim Turban și Ramesh Sharda adoptă o perspectivă agnostic-tehnologică, fiind orientată către procesul decizional. Considerăm că integrarea studiilor de caz din domenii variate, de la agricultură la industria jocurilor video, demonstrează versatilitatea metodelor de Business Intelligence în organizații moderne, indiferent de profilul lor.

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Specificații

ISBN-13: 9781292459295
ISBN-10: 1292459298
Pagini: 736
Dimensiuni: 204 x 253 x 30 mm
Greutate: 1.32 kg
Ediția:5. Auflage
Editura: Pearson Education

De ce să citești această carte

Recomandăm această lucrare profesioniștilor care doresc să facă tranziția către roluri manageriale bazate pe date. Veți câștiga o înțelegere clară a modului în care AI și Data Science pot fi justificate economic și implementate tehnic. Este un resursar complet care transformă conceptele abstracte în instrumente practice de optimizare a performanței organizaționale, punând un accent deosebit pe etică și confidențialitate.

Despre autor

Echipa de autori este formată din academicieni de renume în domeniul sistemelor de suport decizional. Dursun Delen este recunoscut pentru expertiza sa în data mining și analytics, fiind autorul unor lucrări fundamentale în domeniu. Efraim Turban este un pionier în sistemele informatice de management, cu o activitate publicistică vastă ce acoperă comerțul electronic și inteligența artificială aplicată. Ramesh Sharda completează echipa cu o experiență solidă în modelarea decizională și tehnologii analitice, contribuind la formarea a generații de lideri în domeniul Business Intelligence prin intermediul rețelei Pearson Education.

Notă biografică

About our authors Ramesh Sharda (MBA, PhD, University of WisconsinMadison) is the Vice Dean for Research and Graduate Programs, Watson/ConocoPhillips Chair, and a Regents Professor of Management Science and Information Systems in the Spears School of Business at Oklahoma State University (OSU). He cofounded and directed OSU's PhD in Business for the Executives Program. About 200 papers describing his research have been published in major journals, including Operations Research, Management Science, Information Systems Research, Decision Support Systems, and the Journal of MIS. He cofounded the AIS SIG on Decision Support Systems and Knowledge Management (SIGDSA). Dr. Sharda serves on several editorial boards, including those of Decision Support Systems and ACM Data Base. He has authored and edited several textbooks and research books and serves as the coeditor of several Springer book series (Integrated Series in Information Systems, Operations Research/Computer Science Interfaces, and Annals of Information Systems) with Springer. He served as the Executive Director of the Teradata University Network from 2013-2020. His current research interests are in decision support systems, business analytics, and technologies for managing information overload. Ramesh is a Fellow of INFORMS and AIS, and was inducted into the Oklahoma Higher Education Hall of Fame in 2015. He was awarded a Fulbright Distinguished Chair at Aalto University of Finland for spring 2023.
Dursun Delen (PhD, Oklahoma State University) is the Spears Endowed Chair in Business Administration, Patterson Foundation Endowed Chair in Business Analytics, Director of Research for the Center for Health Systems Innovation, and Regents Professor of Management Science and Information Systems in the Spears School of Business at Oklahoma State University (OSU). Prior to his academic career, he worked for a privately owned research and consultancy company, Knowledge Based Systems Inc., in College Station, Texas, as a research scientist for 5 years, during which he led a number of decision support and other information systemsrelated research projects funded by several federal agencies including the Department of Defense (DoD), National Aeronautics and Space Administration (NASA), National Institute for Standards and Technology (NIST), Ballistic Missile Defense Organization (BMDO), and Department of Energy (DOE). Dr. Delen has published more than 200 peer-reviewed articles, some of which have appeared in major journals like Decision Sciences, Decision Support Systems, Communications of the ACM, Computers and Operations Research, Computers in Industry, Journal of Production Operations Management, Artificial Intelligence in Medicine, International Journal of Medical Informatics, Expert Systems with Applications, and IEEE Wireless Communications. He recently authored/coauthored twelve textbooks in the broad areas of business analytics, data mining, text mining, business intelligence, and decision support systems. He is often invited to national and international conferences for keynote addresses on topics related to data/text mining, business analytics, decision support systems, business intelligence, and knowledge management. He regularly chairs, tracks, and minitracks at various information systems and analytics conferences. He is currently serving as the Editor-in-Chief for the Journal of Business Analytics, Journal of AI in Business (part of Frontiers in AI family of journals), and as Senior Editor, Associate Editor, or Editorial Board Member for more than another dozen of academic journals. His research and teaching interests are in data and text mining, business analytics, decision support systems, data science, knowledge management, business intelligence, and enterprise modeling.
Efraim Turban (MBA, PhD., University of California, Berkeley) is a Visiting Scholar at the Pacific Institute for Information System Management, University of Hawaii. Prior to this, he was on the staff of several universities, including City University of Hong Kong; Lehigh University; Florida International University; California State University, Long Beach; Eastern Illinois University; and the University of Southern California. Dr. Turban is the author of more than 100 refereed papers published in leading journals, such as Management Science, MIS Quarterly, and Decision Support Systems. He is also the author of 20 books, including Electronic Commerce: A Managerial Perspective and Information Technology for Management. He is also a consultant to major corporations worldwide. Dr. Turban's current areas of interest are Web-based decision support systems, social commerce, and collaborative decision making.

Cuprins

  1. An Overview of Business Intelligence, Analytics, Data Science, and AI
  2. Artificial Intelligence: Concepts, Drivers, Major Technologies, and Business Applications
  3. Descriptive Analytics I: Nature of Data, Big Data, and Statistical Modeling
  4. Descriptive Analytics II: Business Intelligence Data Warehousing, and Visualization
  5. Predictive Analytics I: Data Mining Process, Methods, and Algorithms
  6. Predictive Analytics II: Text, Web, and Social Media Analytics
  7. Deep Learning and Cognitive Computing
  8. Prescriptive Analytics: Optimization and Simulation
  9. Landscape of Business Analytics Tools
  10. AI-Based Trends in Analytics and Data Science
  11. Ethical, Privacy, and Managerial Considerations in Analytics

Descriere

Business Intelligence, Analytics, Data Science, and AI is your guide to the business-related impact of artificial intelligence, data science and analytics, designed to prepare you for a managerial role. The text's vignettes and cases feature modern companies and non-profit organizations and illustrate capabilities, costs and justifications of BI across various business units. With coverage of many data science/AI applications, you'll explore tools, then learn from various organizations' experiences employing such applications. Ample hands-on practice is provided, can be completed with a range of software, and will help you use analytics as a future manager. The 5th Edition integrates the fully updated content of Analytics, Data Science, and Artificial Intelligence, 11/e and Business Intelligence, Analytics, and Data Science, 4/e into one textbook, strengthened by 4 new chapters that will equip you for today's analytics and AI tech, such as ChatGPT. Examples explore analytics in sports, gaming, agriculture and "data for good."