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5 books on AI for Business Intelligence [PDF]
October 23, 2024 | 21 |
These books are covering various aspects of AI's role in business analytics and transforming data into actionable insights for decision-makers.
1. Artificial Intelligence with Microsoft Power BI
2024 by Jen Stirrup, Thomas J. Weinandy
"Artificial Intelligence with Microsoft Power BI" is a practical guide aimed at enhancing Power BI skills through the integration of AI at a practical level. Targeted at business-oriented software engineers and developers, the book equips readers with essential terminologies, practices and strategies needed to effectively incorporate AI into their business intelligence frameworks. Co-authored by Jen Stirrup, CEO of Data Relish and Thomas Weinandy, research economist at Upside, this resource leverages existing data within organizations to elevate technical capabilities using Microsoft Power BI. Readers will learn to select appropriate AI models, assess their value and ensure validity within their BI environments. The book covers building robust data models, clarifying essential AI concepts, defining project roles and responsibilities, implementing AI models like supervised machine learning and utilizing Azure ML for model development and integration into Power BI. Ultimately, it aims to enhance business AI maturity levels through actionable insights and the AI feedback loop, empowering readers to initiate and advance AI projects effectively.
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2. Artificial Intelligence for Business Analytics: Algorithms, Platforms and Application Scenarios
2023 by Felix Weber
"This book offers a succinct introduction to the essential aspects of leveraging artificial intelligence techniques for business analytics. It presents machine learning concepts and critical algorithms in an accessible manner within the context of business analytics technology. Furthermore, the book provides diverse application scenarios across various industries. Notably, it introduces the Business Analytics Model for Artificial Intelligence, serving as a reference procedure model for structuring business analytics and artificial intelligence projects within organizations. As businesses evolve, relying solely on traditional business intelligence and retrospective insights will no longer suffice. To remain competitive, companies must embrace business analytics, encompassing predictive analyses, automated decision-making and the efficient use of vast datasets—an area where artificial intelligence methods play a pivotal role."
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3. AI-Powered Business Intelligence
2022 by Tobias Zwingmann
In this hands-on guide enriched with practical examples in Power BI, alongside essential Python and R code, you'll delve into the realm of "AI-Powered Business Intelligence." Within these pages, you'll uncover the most pertinent AI applications in the realm of Business Intelligence, encompassing enhancements in forecasting, automated categorization and AI-driven recommendations. The book equips BI professionals, business analysts and data analytics enthusiasts with insights into the pivotal domains of artificial intelligence, propelling them into the world of high-impact AI solutions. Renowned author Tobias Zwingmann facilitates an understanding of how to harness the potential of AI. You'll gain expertise in leveraging popular AI-as-a-service and AutoML platforms to execute enterprise-grade proofs of concept autonomously, without the reliance on software engineers or data scientists. This book empowers you to unlock the business potential of AI within BI environments, employing AutoML for streamlined classification and advanced forecasting, implementing recommendation services, unraveling insights from extensive text data through NLP services, extracting knowledge from documents and images via computer vision services and constructing interactive user interfaces for AI-driven dashboard prototypes. It also guides you through a comprehensive case study, illustrating the construction of an AI-powered customer analytics dashboard from inception to implementation.
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4. Decision Intelligence Analytics and the Implementation of Strategic Business Management
2022 by P. Mary Jeyanthi, Tanupriya Choudhury, Dieu Hack-Polay, T P Singh, Sheikh Abujar
This book introduces a comprehensive framework for crafting an analytics strategy that encompasses a spectrum of activities, spanning from defining problems and gathering data to establishing data repositories, conducting analyses and facilitating effective decision-making processes. Within its pages, the authors delve into exemplary practices for orchestrating team analytics strategies, encompassing domains like player assessment, game tactics, training and performance evaluation. Furthermore, they probe into the ways in which organizations can leverage analytics to bolster revenue streams and streamline their operations for heightened efficiency. The book equips readers with the essential insights to construct and structure a decision intelligence analytics system capable of illuminating every facet of an organization. It delves into the criteria and tools for appraising and choosing decision intelligence analytics technologies, along with strategies for cultivating a corporate culture that champions data-driven decision-making. Each chapter is thoughtfully organized to provide readers with an in-depth understanding of business intelligence, decision-making and artificial intelligence within the context of strategic management.
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5. Machine Learning and Cognition in Enterprises: Business Intelligence Transformed
2017 by Rohit Kumar
In this book, author Rohit Kumar delves into the complex intersection of machine learning and cognition within IT systems, offering comprehensive descriptions and real-world business scenarios. The journey begins with an exploration of the origins of artificial intelligence and its evolution into cognitive computing. Kumar provides a thorough examination of machine learning, elucidating the motivations behind evolving business models to incorporate it and emphasizing its significance for modern enterprises. Throughout the book, readers gain proficiency in the nuances of natural language processing, predictive analytics and cognitive computing. Each technique is meticulously explained, empowering organizations to seamlessly integrate them into their operations as needed. This practical guide serves as a roadmap for business transformation through cognitive computing, enabling enterprises to navigate confidently within a constantly evolving business landscape. It is an invaluable resource for business managers and leadership teams seeking to harness the potential of machine learning and cognitive computing. Master the details of modern AI as it applies to enterprisesMap the path ahead in terms of your IT-business integrationAvoid common road blocks in the process of adopting cognitive computing in your business Who This Book Is For Business managers and leadership teams.
Download PDF
How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
1. Artificial Intelligence with Microsoft Power BI
2024 by Jen Stirrup, Thomas J. Weinandy
"Artificial Intelligence with Microsoft Power BI" is a practical guide aimed at enhancing Power BI skills through the integration of AI at a practical level. Targeted at business-oriented software engineers and developers, the book equips readers with essential terminologies, practices and strategies needed to effectively incorporate AI into their business intelligence frameworks. Co-authored by Jen Stirrup, CEO of Data Relish and Thomas Weinandy, research economist at Upside, this resource leverages existing data within organizations to elevate technical capabilities using Microsoft Power BI. Readers will learn to select appropriate AI models, assess their value and ensure validity within their BI environments. The book covers building robust data models, clarifying essential AI concepts, defining project roles and responsibilities, implementing AI models like supervised machine learning and utilizing Azure ML for model development and integration into Power BI. Ultimately, it aims to enhance business AI maturity levels through actionable insights and the AI feedback loop, empowering readers to initiate and advance AI projects effectively.
Download PDF
2. Artificial Intelligence for Business Analytics: Algorithms, Platforms and Application Scenarios
2023 by Felix Weber
"This book offers a succinct introduction to the essential aspects of leveraging artificial intelligence techniques for business analytics. It presents machine learning concepts and critical algorithms in an accessible manner within the context of business analytics technology. Furthermore, the book provides diverse application scenarios across various industries. Notably, it introduces the Business Analytics Model for Artificial Intelligence, serving as a reference procedure model for structuring business analytics and artificial intelligence projects within organizations. As businesses evolve, relying solely on traditional business intelligence and retrospective insights will no longer suffice. To remain competitive, companies must embrace business analytics, encompassing predictive analyses, automated decision-making and the efficient use of vast datasets—an area where artificial intelligence methods play a pivotal role."
Download PDF
3. AI-Powered Business Intelligence
2022 by Tobias Zwingmann
In this hands-on guide enriched with practical examples in Power BI, alongside essential Python and R code, you'll delve into the realm of "AI-Powered Business Intelligence." Within these pages, you'll uncover the most pertinent AI applications in the realm of Business Intelligence, encompassing enhancements in forecasting, automated categorization and AI-driven recommendations. The book equips BI professionals, business analysts and data analytics enthusiasts with insights into the pivotal domains of artificial intelligence, propelling them into the world of high-impact AI solutions. Renowned author Tobias Zwingmann facilitates an understanding of how to harness the potential of AI. You'll gain expertise in leveraging popular AI-as-a-service and AutoML platforms to execute enterprise-grade proofs of concept autonomously, without the reliance on software engineers or data scientists. This book empowers you to unlock the business potential of AI within BI environments, employing AutoML for streamlined classification and advanced forecasting, implementing recommendation services, unraveling insights from extensive text data through NLP services, extracting knowledge from documents and images via computer vision services and constructing interactive user interfaces for AI-driven dashboard prototypes. It also guides you through a comprehensive case study, illustrating the construction of an AI-powered customer analytics dashboard from inception to implementation.
Download PDF
4. Decision Intelligence Analytics and the Implementation of Strategic Business Management
2022 by P. Mary Jeyanthi, Tanupriya Choudhury, Dieu Hack-Polay, T P Singh, Sheikh Abujar
This book introduces a comprehensive framework for crafting an analytics strategy that encompasses a spectrum of activities, spanning from defining problems and gathering data to establishing data repositories, conducting analyses and facilitating effective decision-making processes. Within its pages, the authors delve into exemplary practices for orchestrating team analytics strategies, encompassing domains like player assessment, game tactics, training and performance evaluation. Furthermore, they probe into the ways in which organizations can leverage analytics to bolster revenue streams and streamline their operations for heightened efficiency. The book equips readers with the essential insights to construct and structure a decision intelligence analytics system capable of illuminating every facet of an organization. It delves into the criteria and tools for appraising and choosing decision intelligence analytics technologies, along with strategies for cultivating a corporate culture that champions data-driven decision-making. Each chapter is thoughtfully organized to provide readers with an in-depth understanding of business intelligence, decision-making and artificial intelligence within the context of strategic management.
Download PDF
5. Machine Learning and Cognition in Enterprises: Business Intelligence Transformed
2017 by Rohit Kumar
In this book, author Rohit Kumar delves into the complex intersection of machine learning and cognition within IT systems, offering comprehensive descriptions and real-world business scenarios. The journey begins with an exploration of the origins of artificial intelligence and its evolution into cognitive computing. Kumar provides a thorough examination of machine learning, elucidating the motivations behind evolving business models to incorporate it and emphasizing its significance for modern enterprises. Throughout the book, readers gain proficiency in the nuances of natural language processing, predictive analytics and cognitive computing. Each technique is meticulously explained, empowering organizations to seamlessly integrate them into their operations as needed. This practical guide serves as a roadmap for business transformation through cognitive computing, enabling enterprises to navigate confidently within a constantly evolving business landscape. It is an invaluable resource for business managers and leadership teams seeking to harness the potential of machine learning and cognitive computing. Master the details of modern AI as it applies to enterprisesMap the path ahead in terms of your IT-business integrationAvoid common road blocks in the process of adopting cognitive computing in your business Who This Book Is For Business managers and leadership teams.
Download PDF
How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
