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220317 ||| eng |
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|a 9781119736097
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|a 9781119736103
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|a 1119736102
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|a 9781119736110
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4 |
|a HF5548.2
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|a Maisel, Lawrence
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| 245 |
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|a AI-enabled analytics for business
|b a roadmap for becoming an analytics powerhouse
|c Lawrence S. Maisel, Robert J. Zwerling, Jesper H. Sorensen
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| 260 |
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|a Hoboken, New Jersey
|b John Wiley & Sons, Inc.
|c 2022
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| 300 |
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|a 1 online resource
|b color illustrations
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| 505 |
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|a Includes bibliographical references and index
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|a Part 1: Fundamentals -- Chapter 1 -- A Primer on AI-Enabled Analytics for Business -- Chapter 2 -- Why AI-Enabled Analytics Is Essential for Business -- Chapter 3 -- Myths and Misconceptions about Analytics -- Chapter 4 -- Applications of AI-Enabled Analytics -- Part 2: Roadmap -- Chapter 5 -- Roadmap for How to Implement AI-Enabled Analytics in Business -- Chapter 6 -- Executive Responsibilities to Implement Analytics -- Chapter 7 -- Implementing Analytics -- Chapter 8 -- The Role of Analytics in Strategic Decisions -- Part 3: Use Cases -- Chapter 9 -- Cases of Analytics Failures from Deviation to the Roadmap -- Chapter 10 -- Use Case: Grabbing Defeat from the Jaws of Victory -- Chapter 11 -- Use Case: Incremental Improvements to Gain Insights -- Chapter 12 -- Use Case: Analytics Are for Everyone
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| 653 |
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|a Gestion / Informatique
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| 653 |
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|a Artificial intelligence / Marketing applications / fast
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| 653 |
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|a Intelligence artificielle / Applications en marketing
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| 653 |
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|a Artificial intelligence / Marketing applications / http://id.loc.gov/authorities/subjects/sh2020008033
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| 653 |
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|a Artificial intelligence / Industrial applications
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| 653 |
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|a Artificial intelligence / Industrial applications / fast
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| 653 |
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|a Business / Data processing / http://id.loc.gov/authorities/subjects/sh85018264
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| 653 |
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|a Intelligence artificielle / Applications industrielles
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| 653 |
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|a Business / Data processing / fast
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| 700 |
1 |
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|a Zwerling, Robert James
|e author
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| 700 |
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|a Sorensen, Jesper Hybholt
|e author
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| 041 |
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7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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| 776 |
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|z 9781119736080
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| 776 |
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|z 9781119736097
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| 776 |
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|z 1119736080
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| 776 |
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|z 9781119736103
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|u https://learning.oreilly.com/library/view/~/9781119736080/?ar
|x Verlag
|3 Volltext
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|a 658
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|a 381
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|a 658/.05
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|a 330
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|a "Predictive business analytics refers to the skills, technologies, tools, and processes for continuous analysis of past business performance to gain forward-looking insight and drive business decisions and actions. It focuses on developing new insights and understanding business performance based on extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling, and fact-based management as input for human decisions--or it may drive fully automated decisions. We are entering the era of digital analytics where human and artificial intelligence (AI) work hand in hand to achieve better analytical results. Today, more than ever, businesses are expected to possess the talent, tools, processes, and capabilities to enable their organizations to implement and utilize continuous analysis of past business performance and events to gain forward-looking insight to drive business decisions and actions. More and more organizations are seeking better processes and tools to ensure that the right people have the right information at the right time, to make smarter decisions. This process, in essence, reflects an organizational capability to improve managerial decision making across many core performance and financial areas. For years, organizations have sought to develop and deploy an effective process to capture and filter forward-looking measures that enable it to understand significant patterns, relationships, and trends in order to facilitate better and more insightful decisions about the future. This book is intended to promote clarity and ensure that the application of AI-Enabled Predictive Business Analytics is relevant to all business functions"--
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