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AI-Enabled Analytics for Business : A Roadmap for Becoming an Analytics Powerhouse

Authors :
Lawrence S. Maisel
Robert J. Zwerling
Jesper H. Sorensen
Lawrence S. Maisel
Robert J. Zwerling
Jesper H. Sorensen
Publication Year :
2022

Abstract

We are entering the era of digital transformation where human and artificial intelligence (AI) work hand in hand to achieve data driven performance. 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. AI-Enabled Analytics in Business is your Roadmap to meet this essential business capability. To ensure we can plan for the future vs react to the future when it arrives, we need to develop and deploy a toolbox of tools, techniques, and effective processes to reveal forward-looking unbiased insights that help us understand significant patterns, relationships, and trends. This book promotes clarity to enable you to make better decisions from insights about the future. Learn how advanced analytics ensures that your people have the right information at the right time to gain critical insights and performance opportunities Empower better, smarter decision making by implementing AI-enabled analytics decision support tools Uncover patterns and insights in data, and discover facts about your business that will unlock greater performance Gain inspiration from practical examples and use cases showing how to move your business toward AI-Enabled decision making AI-Enabled Analytics in Business is a must-have practical resource for directors, officers, and executives across various functional disciplines who seek increased business performance and valuation.

Details

Language :
English
ISBNs :
9781119736080, 9781119736097, and 9781119736103
Database :
eBook Index
Journal :
AI-Enabled Analytics for Business : A Roadmap for Becoming an Analytics Powerhouse
Publication Type :
eBook
Accession number :
3139479