Artificial Intelligence For Business Analytics

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Artificial Intelligence For Business Analytics

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Author : Felix Weber
language : en
Publisher: Springer Nature
Release Date : 2023-03-01

Artificial Intelligence For Business Analytics written by Felix Weber and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-01 with Computers categories.

While methods of artificial intelligence (AI) were until a few years ago exclusively a topic of scientific discussions, today they are increasingly finding their way into products of everyday life. At the same time, the amount of data produced and available is growing due to increasing digitalization, the integration of digital measurement and control systems, and automatic exchange between devices (Internet of Things). In the future, the use of business intelligence (BI) and a look into the past will no longer be sufficient for most companies.Instead, business analytics, i.e., predictive and predictive analyses and automated decisions, will be needed to stay competitive in the future. The use of growing amounts of data is a significant challenge and one of the most important areas of data analysis is represented by artificial intelligence methods.This book provides a concise introduction to the essential aspects of using artificial intelligence methods for business analytics, presents machine learning and the most important algorithms in a comprehensible form using the business analytics technology framework, and shows application scenarios from various industries. In addition, it provides the Business Analytics Model for Artificial Intelligence, a reference procedure model for structuring BA and AI projects in the company. This book is a translation of the original German 1st edition Künstliche Intelligenz für Business Analytics by Felix Weber, published by Springer Fachmedien Wiesbaden GmbH, part of Springer Nature in 2020. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation. Springer Nature works continuously to further the development of tools for the production of books and on the related technologies to support the authors.

Ai And Business Analytics Leveraging Machine Learning For Enhanced Business Intelligence

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Author : SHACHI GHANSHYAM SAYATA, DR. ABHISHEK SINGH VERMA
language : en
Publisher: DeepMisti Publication
Release Date : 2025-01-22

Ai And Business Analytics Leveraging Machine Learning For Enhanced Business Intelligence written by SHACHI GHANSHYAM SAYATA, DR. ABHISHEK SINGH VERMA and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-22 with Computers categories.

In the ever-evolving world of business, data has emerged as one of the most valuable assets. With businesses generating an immense amount of data every day, the challenge lies in turning this data into actionable insights that drive informed decision-making. The convergence of Artificial Intelligence (AI) and business analytics provides a transformative approach to harnessing the potential of data, making it possible for organizations to gain deeper insights, enhance operational efficiency, and innovate in their strategies. "AI and Business Analytics: Leveraging Machine Learning for Enhanced Business Intelligence" explores this powerful intersection, offering a comprehensive understanding of how machine learning (ML) techniques are being utilized to revolutionize the business landscape. The book, authored by Shachi Ghanshyam Sayata and Dr. Abhishek Singh Verma, delves into the theoretical underpinnings of AI and ML while providing practical applications for businesses striving to gain a competitive edge in an increasingly data-driven world. The authors bring their expertise to the forefront by discussing a wide array of topics, from the basics of machine learning algorithms to their advanced applications in real-world business scenarios. The integration of AI in business intelligence allows companies to make predictions, optimize processes, and personalize customer experiences with unprecedented accuracy. As the digital transformation accelerates, businesses are adopting AI-driven analytics to stay ahead of market trends, anticipate challenges, and uncover new opportunities. This book aims to serve as a valuable resource for professionals, researchers, and students alike. It offers a balanced mix of theoretical concepts and hands-on applications, ensuring readers not only grasp the fundamental principles of AI and ML but also learn how to implement these techniques in business environments effectively. It is particularly relevant for those seeking to understand the practical integration of these technologies into business operations, and how AI can lead to smarter decision-making processes that ultimately drive growth and success. In summary, "AI and Business Analytics" provides the necessary tools and insights for leveraging machine learning technologies to unlock the full potential of business intelligence. The authors’ collective expertise and practical approach make this book an indispensable guide for anyone looking to explore the dynamic fusion of AI, business analytics, and machine learning in today’s rapidly changing business world. We hope that this work will inspire both the academic and professional community to engage with these exciting technologies, thereby contributing to the next generation of AI-powered business innovations. Authors

Computational Intelligence For Business Analytics

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Author : Witold Pedrycz
language : en
Publisher: Springer Nature
Release Date : 2021-10-26

Computational Intelligence For Business Analytics written by Witold Pedrycz and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-26 with Technology & Engineering categories.

Corporate success has been changed by the importance of new developments in Business Analytics (BA) and furthermore by the support of computational intelligence- based techniques. This book opens a new avenues in these subjects, identifies key developments and opportunities. The book will be of interest for students, researchers and professionals to identify innovative ways delivered by Business Analytics based on computational intelligence solutions. They help elicit information, handle knowledge and support decision-making for more informed and reliable decisions even under high uncertainty environments.Computational Intelligence for Business Analytics has collected the latest technological innovations in the field of BA to improve business models related to Group Decision-Making, Forecasting, Risk Management, Knowledge Discovery, Data Breach Detection, Social Well-Being, among other key topics related to this field.

Generative Ai For Business Analytics And Strategic Decision Making In Service Industry

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Author : Venaik, Anita
language : en
Publisher: IGI Global
Release Date : 2025-01-31

Generative Ai For Business Analytics And Strategic Decision Making In Service Industry written by Venaik, Anita and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-31 with Business & Economics categories.

Generative AI is transforming industries by enhancing how businesses analyze data, generate content, and automate complex processes. Its ability to produce diverse, high-quality outputs in areas like marketing, customer engagement, and software development is reshaping productivity and innovation. By leveraging advanced models such as GANs and Transformers, organizations can unlock new insights, streamline decision-making, and personalize services at scale. Generative AI also plays a crucial role in detecting errors, managing knowledge, and mitigating harmful content, contributing to safer and more efficient digital environments. This technology not only accelerates growth but also democratizes access to powerful tools, fostering creativity and problem-solving across sectors. Generative AI for Business Analytics and Strategic Decision Making in Service Industry provides a comprehensive exploration of how generative AI techniques can revolutionize business intelligence and data analytics practices. It offers a detailed examination of innovative algorithms, methodologies, and tools for leveraging generative AI to extract actionable insights, drive innovation, and enhance decision-making processes within the service industry. Covering topics such as big data, generative adversarial networks (GANs), and productivity management, this book is an excellent resource for students, academicians, industry professionals, researchers, managers, and more.

Artificial Intelligence For Business

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Author : Rajendra Akerkar
language : en
Publisher: Springer
Release Date : 2018-08-11

Artificial Intelligence For Business written by Rajendra Akerkar and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-11 with Business & Economics categories.

This book offers a practical guide to artificial intelligence (AI) techniques that are used in business. The book does not focus on AI models and algorithms, but instead provides an overview of the most popular and frequently used models in business. This allows the book to easily explain AI paradigms and concepts for business students and executives. Artificial Intelligence for Business is divided into six chapters. Chapter 1 begins with a brief introduction to AI and describes its relationship with machine learning, data science and big data analytics. Chapter 2 presents core machine learning workflow and the most effective machine learning techniques. Chapter 3 deals with deep learning, a popular technique for developing AI applications. Chapter 4 introduces recommendation engines for business and covers how to use them to be more competitive. Chapter 5 features natural language processing (NLP) for sentiment analysis focused on emotions. With the help of sentiment analysis, businesses can understand their customers better to improve their experience, which will help the businesses change their market position. Chapter 6 states potential business prospects of AI and the benefits that companies can realize by implementing AI in their processes.

Machine Learning For Business Analytics

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Author : Hemachandran K
language : en
Publisher: CRC Press
Release Date : 2022-07-21

Machine Learning For Business Analytics written by Hemachandran K and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-21 with Business & Economics categories.

Machine Learning is an integral tool in a business analyst’s arsenal because the rate at which data is being generated from different sources is increasing and working on complex unstructured data is becoming inevitable. Data collection, data cleaning, and data mining are rapidly becoming more difficult to analyze than just importing information from a primary or secondary source. The machine learning model plays a crucial role in predicting the future performance and results of a company. In real-time, data collection and data wrangling are the important steps in deploying the models. Analytics is a tool for visualizing and steering data and statistics. Business analysts can work with different datasets -- choosing an appropriate machine learning model results in accurate analyzing, forecasting the future, and making informed decisions. The global machine learning market was valued at $1.58 billion in 2017 and is expected to reach $20.83 billion in 2024 -- growing at a CAGR of 44.06% between 2017 and 2024. The authors have compiled important knowledge on machine learning real-time applications in business analytics. This book enables readers to get broad knowledge in the field of machine learning models and to carry out their future research work. The future trends of machine learning for business analytics are explained with real case studies. Essentially, this book acts as a guide to all business analysts. The authors blend the basics of data analytics and machine learning and extend its application to business analytics. This book acts as a superb introduction and covers the applications and implications of machine learning. The authors provide first-hand experience of the applications of machine learning for business analytics in the section on real-time analysis. Case studies put the theory into practice so that you may receive hands-on experience with machine learning and data analytics. This book is a valuable source for practitioners, industrialists, technologists, and researchers.

Artificial Intelligence Business Applications

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Author : Oliver Tensor
language : en
Publisher: Smart Creative Publishing
Release Date : 2020-10-13

Artificial Intelligence Business Applications written by Oliver Tensor and has been published by Smart Creative Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-13 with categories.

Do you want to learn the progress made in the web marketing space and how you can exploit it for your marketing strategies? Do you want to gain an edge over your business's competitors? If you want to know how Artificial Intelligence Technology can give your business a major performance boost, then keep reading. The Fourth Industrial Revolution is upon us, led by the Artificial Intelligence technology and setting the humankind for a global social transformation. The powerful applications of AI have already transformed our daily lives. Tools such as virtual personal and home assistants (like Siri in Apple Pods and Alexa in Amazon Echo) have become everyday usage products. Moreover, our digital lives have inundated organizations with astronomical volumes of data with hidden treasures of valuable insights. This information can be uncovered with the use of big data analytics and applied in combination with the Artificial Intelligence technology to increase your business performance efficiency. Learning to incorporate the Artificial Intelligence applications, Machine Learning, and Big Data Analytics in line with your company's domain can only give your business positive results. Our aim with this book is to provide you a 360 view of the fundamentals and importance of Artificial Intelligence Technology. You Will Learn: The Fundamentals of Artificial Intelligence and Machine Learning Applications, and Why are They so Important in the World Today. Gain an In-depth Understanding of 12 of the Most Popular Artificial Intelligence Tools in the Market, in an Easy to Understand and Colloquial Language. The Science of Big Data and How Companies are Increasingly Employing Good Analytical Tools to Makes Sense of an Estimated 1.7 MB of Data that will be Generated per Second per Person by 2020. What Different Types of Machine Learning Algorithms are and How They Work to Make Machines Able to Learn and Train themselves with Repeated Use. Even if you are a beginner, you will be armed to make sound personal and professional technological choices. Would You Like to Know More? Download Now to get access to Artificial Intelligence power.

Building Analytics Teams

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Author : John K. Thompson
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-06-30

Building Analytics Teams written by John K. Thompson and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-30 with Computers categories.

Master the skills necessary to hire and manage a team of highly skilled individuals to design, build, and implement applications and systems based on advanced analytics and AI Key FeaturesLearn to create an operationally effective advanced analytics team in a corporate environmentSelect and undertake projects that have a high probability of success and deliver the improved top and bottom-line resultsUnderstand how to create relationships with executives, senior managers, peers, and subject matter experts that lead to team collaboration, increased funding, and long-term success for you and your teamBook Description In Building Analytics Teams, John K. Thompson, with his 30+ years of experience and expertise, illustrates the fundamental concepts of building and managing a high-performance analytics team, including what to do, who to hire, projects to undertake, and what to avoid in the journey of building an analytically sound team. The core processes in creating an effective analytics team and the importance of the business decision-making life cycle are explored to help achieve initial and sustainable success. The book demonstrates the various traits of a successful and high-performing analytics team and then delineates the path to achieve this with insights on the mindset, advanced analytics models, and predictions based on data analytics. It also emphasizes the significance of the macro and micro processes required to evolve in response to rapidly changing business needs. The book dives into the methods and practices of managing, developing, and leading an analytics team. Once you've brought the team up to speed, the book explains how to govern executive expectations and select winning projects. By the end of this book, you will have acquired the knowledge to create an effective business analytics team and develop a production environment that delivers ongoing operational improvements for your organization. What you will learnAvoid organizational and technological pitfalls of moving from a defined project to a production environmentEnable team members to focus on higher-value work and tasksBuild Advanced Analytics and Artificial Intelligence (AA&AI) functions in an organizationOutsource certain projects to competent and capable third partiesSupport the operational areas that intend to invest in business intelligence, descriptive statistics, and small-scale predictive analyticsAnalyze the operational area, the processes, the data, and the organizational resistanceWho this book is for This book is for senior executives, senior and junior managers, and those who are working as part of a team that is accountable for designing, building, delivering and ensuring business success through advanced analytics and artificial intelligence systems and applications. At least 5 to 10 years of experience in driving your organization to a higher level of efficiency will be helpful.

Leading With Ai And Analytics Build Your Data Science Iq To Drive Business Value

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Author : Eric Anderson
language : en
Publisher: McGraw Hill Professional
Release Date : 2020-11-23

Leading With Ai And Analytics Build Your Data Science Iq To Drive Business Value written by Eric Anderson and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-23 with Business & Economics categories.

Lead your organization to become evidence-driven Data. It’s the benchmark that informs corporate projections, decision-making, and analysis. But, why do many organizations that see themselves as data-driven fail to thrive? In Leading with AI and Analytics, two renowned experts from the Kellogg School of Management show business leaders how to transform their organization to become evidence-driven, which leads to real, measurable changes that can help propel their companies to the top of their industries. The availability of unprecedented technology-enabled tools has made AI (Artificial Intelligence) an essential component of business analytics. But what’s often lacking are the leadership skills to integrate these technologies to achieve maximum value. Here, the authors provide a comprehensive game plan for developing that all-important human factor to get at the heart of data science: the ability to apply analytical thinking to real-world problems. Each of these tools and techniques comes to powerful life through a wealth of powerful case studies and real-world success stories. Inside, you’ll find the essential tools to help you: Develop a strong data science intuition quotient Lead and scale AI and analytics throughout your organization Move from “best-guess” decision making to evidence-based decisions Craft strategies and tactics to create real impact Written for anyone in a leadership or management role—from C-level/unit team managers to rising talent—this powerful, hands-on guide meets today’s growing need for real-world tools to lead and succeed with data.

New Paradigms In Big Data Technology And Business Analytics

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Author : Srikanta Patnaik
language : en
Publisher: Springer Nature
Release Date : 2025-07-11

New Paradigms In Big Data Technology And Business Analytics written by Srikanta Patnaik and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-11 with Computers categories.

“New Paradigms in Big Data Technology and Business Analytics” emphasize the integration of Big Data Technology and Business Analytics enables organizations to transform vast volumes of data into strategic insights, driving smarter decisions, operational efficiency, and innovative growth. This volume presents a comprehensive exploration of the evolving landscape of Big Data Technology and Business Analytics, showcasing transformative approaches that are reshaping industries and research alike. It highlights the integration of advanced tools such as artificial intelligence, machine learning, data mining, and cloud infrastructure to drive intelligent decision-making and operational efficiency. Focusing on both theoretical frameworks and real-world case studies, this book explores into five essential domains: Big Data Infrastructure and Technologies, Data Mining and Machine Learning, Big Data Applications and Case Studies, Business Intelligence and Decision Support, and Data Governance and Ethics. By merging theoretical knowledge with practical applications, this book equips educators, researchers, practitioners, and students with actionable insights into how data-driven strategies can unlock sustainable growth and innovation across sectors. With a forward-thinking vision, it addresses key issues like data privacy, algorithmic fairness, and strategic deployment of analytics in diverse environments. By blending emerging technologies with practical applications, this book serves as a roadmap for anyone aiming to harness the full potential of big data to reshape modern business and society.