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AI-Powered Business Intelligence: Revolutionizing Data Analysis and Decision-Making
Author: Dr. Evelyn Reed, PhD in Data Science and a leading expert in AI applications within the business intelligence sector. Dr. Reed has over 15 years of experience in developing and implementing AI-driven solutions for Fortune 500 companies and has published numerous articles and studies on the topic of "ai-powered business intelligence pdf" and related subjects.
Publisher: TechInsights Publishing, a reputable publisher known for its high-quality research reports and white papers on emerging technologies, including artificial intelligence and business analytics. TechInsights Publishing maintains a rigorous peer-review process ensuring the accuracy and reliability of its publications.
Editor: Mr. David Chen, a seasoned editor with over 20 years of experience in the technology and business publishing industry. Mr. Chen has a deep understanding of data analytics and has overseen the publication of several impactful reports on "ai-powered business intelligence pdf" and related subjects.
1. Introduction: The Rise of AI in Business Intelligence
The business intelligence (BI) landscape is undergoing a dramatic transformation driven by the rapid advancement and adoption of artificial intelligence (AI). Traditional BI methods, often reliant on manual data analysis and reporting, are increasingly being augmented, and in some cases replaced, by AI-powered tools. This "ai-powered business intelligence pdf" report delves into the impact of AI on BI, exploring its capabilities, challenges, and the resulting benefits for organizations. The increasing availability of data, coupled with the advancements in AI algorithms, has created an environment where intelligent insights can be extracted at an unprecedented scale and speed. Downloading a comprehensive "ai-powered business intelligence pdf" can provide a detailed understanding of these trends.
2. Core Components of AI-Powered Business Intelligence
AI-powered BI solutions leverage several key technologies:
Machine Learning (ML): ML algorithms are crucial for predictive analytics, allowing businesses to forecast future trends, customer behavior, and market conditions. ML models can identify patterns and relationships in data that would be impossible for humans to detect manually. This capability is a major focus of many "ai-powered business intelligence pdf" reports.
Deep Learning (DL): A subset of ML, DL utilizes artificial neural networks with multiple layers to analyze complex data, such as images, text, and audio. DL is particularly useful for tasks like sentiment analysis of customer reviews or image recognition for inventory management. The application of DL is increasingly discussed in "ai-powered business intelligence pdf" documents.
Natural Language Processing (NLP): NLP enables BI systems to understand and interpret human language, allowing users to interact with data using natural language queries. This significantly simplifies data exploration and reporting, removing the need for complex SQL queries or specialized programming skills. The role of NLP is a frequent topic in "ai-powered business intelligence pdf" resources.
Computer Vision: This technology allows BI systems to process and analyze visual data, like images and videos. This is valuable for applications such as inventory management, quality control, and customer behavior analysis in physical stores. The increasing importance of computer vision is highlighted in numerous "ai-powered business intelligence pdf" publications.
3. Applications of AI in Business Intelligence
AI's impact spans various business functions:
Predictive Maintenance: AI can analyze sensor data from machinery to predict potential failures, allowing for proactive maintenance and reducing downtime.
Customer Relationship Management (CRM): AI enhances CRM by personalizing customer interactions, predicting customer churn, and identifying high-value customers.
Supply Chain Optimization: AI optimizes supply chain operations by predicting demand, improving inventory management, and optimizing logistics.
Fraud Detection: AI algorithms can detect fraudulent transactions with high accuracy, reducing financial losses and improving security.
Financial Forecasting: AI models can analyze financial data to predict future performance, inform investment decisions, and manage risk.
Marketing and Sales: AI assists in targeted advertising, lead scoring, and sales forecasting.
4. Benefits of AI-Powered Business Intelligence
Adopting AI-powered BI offers several significant advantages:
Improved Decision-Making: AI provides data-driven insights that facilitate better, more informed decisions.
Increased Efficiency: Automation reduces manual effort and speeds up data analysis.
Enhanced Accuracy: AI minimizes human error and improves the accuracy of insights.
Competitive Advantage: Organizations leveraging AI-powered BI gain a significant competitive edge.
New Revenue Streams: AI can unlock new revenue opportunities by identifying previously unseen market trends and customer needs. These advantages are extensively documented in "ai-powered business intelligence pdf" reports.
5. Challenges and Considerations
Despite the benefits, implementing AI-powered BI presents some challenges:
Data Quality: AI models require high-quality data for accurate results. Poor data quality can lead to inaccurate predictions and flawed insights.
Data Security and Privacy: Protecting sensitive data is crucial when using AI-powered BI systems. Robust security measures are essential.
Integration Complexity: Integrating AI tools with existing BI infrastructure can be complex and require significant technical expertise.
Lack of Skilled Professionals: A shortage of skilled professionals with expertise in AI and BI can hinder adoption.
Explainability and Transparency: Understanding how AI models arrive at their conclusions is crucial for building trust and ensuring accountability. Addressing these challenges is crucial, as discussed in many "ai-powered business intelligence pdf" analyses.
6. Future Trends in AI-Powered Business Intelligence
Future trends include:
Rise of Explainable AI (XAI): Increasing focus on developing AI models that are more transparent and understandable.
Edge Computing: Processing data closer to the source (e.g., on devices) to reduce latency and improve efficiency.
Increased Use of Cloud-Based Solutions: Cloud platforms offer scalable and cost-effective AI and BI solutions.
Integration with IoT Devices: Combining AI with IoT data creates even more powerful insights.
Advancements in NLP and Computer Vision: Continued advancements in these areas will further enhance AI-powered BI capabilities.
7. Case Studies: Real-World Examples
Several successful case studies demonstrate the practical applications of "ai-powered business intelligence pdf" solutions. For instance, a major retailer used AI to optimize its inventory management, reducing stockouts and improving customer satisfaction. A financial institution leveraged AI for fraud detection, significantly reducing its losses. These case studies, frequently featured in "ai-powered business intelligence pdf" documents, showcase the transformative potential of AI in business intelligence.
8. Conclusion
AI is revolutionizing the field of business intelligence, enabling organizations to extract valuable insights from data at an unprecedented scale and speed. By leveraging AI-powered BI solutions, businesses can improve decision-making, increase efficiency, gain a competitive advantage, and unlock new revenue streams. While challenges remain, the future of BI is undeniably intertwined with AI, and those organizations that embrace this technology will be best positioned for success. A thorough understanding of "ai-powered business intelligence pdf" is crucial for navigating this evolving landscape.
9. FAQs
1. What is the difference between traditional BI and AI-powered BI? Traditional BI relies on manual analysis, while AI-powered BI leverages algorithms for automated insights and predictions.
2. What are the key benefits of using AI in BI? Improved decision-making, increased efficiency, enhanced accuracy, competitive advantage, and new revenue streams.
3. What are the biggest challenges in implementing AI-powered BI? Data quality, security, integration complexity, lack of skilled professionals, and explainability.
4. What types of data can AI-powered BI analyze? Structured and unstructured data, including numerical, textual, and visual data.
5. How can AI improve customer experience? Through personalization, targeted marketing, and improved customer service.
6. What are some examples of AI-powered BI tools? Many vendors offer platforms incorporating these capabilities; research specific tools relevant to your needs.
7. How much does it cost to implement AI-powered BI? Costs vary greatly depending on the complexity of the implementation and the chosen tools.
8. What skills are needed to work with AI-powered BI? Data science, data engineering, business analysis, and domain expertise.
9. Where can I find more information on AI-powered BI? Numerous resources are available online, including research papers, articles, and vendor websites; utilizing a search for "ai-powered business intelligence pdf" is a good starting point.
10. Related Articles
1. "The Impact of AI on Business Intelligence: A Comprehensive Review": This article provides a broad overview of AI's impact on various BI aspects, analyzing its applications across different industries.
2. "Predictive Analytics with AI: Driving Business Growth": This article focuses on the application of AI in predictive analytics within BI, illustrating various techniques and their impact on business decision-making.
3. "AI-Driven Customer Segmentation: Enhancing Marketing Effectiveness": This paper examines how AI can improve customer segmentation, leading to more effective marketing strategies and increased ROI.
4. "Building an Effective AI-Powered Business Intelligence System: A Practical Guide": This article offers a step-by-step guide on implementing AI-powered BI solutions, providing practical advice and best practices.
5. "Ethical Considerations in AI-Powered Business Intelligence": This article explores the ethical implications of using AI in BI, addressing issues such as data privacy, bias, and transparency.
6. "The Future of AI in Business Intelligence: Trends and Predictions": This article examines future trends in AI-powered BI, including the rise of explainable AI, edge computing, and integration with IoT devices.
7. "Case Studies in AI-Powered Business Intelligence: Success Stories and Lessons Learned": This article presents several real-world case studies showcasing the successful implementation of AI-powered BI solutions across diverse industries.
8. "Overcoming Challenges in Implementing AI-Powered Business Intelligence": This article discusses the challenges faced during the implementation of AI-powered BI and provides solutions to overcome these hurdles.
9. "AI and Business Intelligence: A Comparative Analysis of Different AI Techniques": This article compares and contrasts various AI techniques used in BI, highlighting their strengths and weaknesses for different applications.
| ai powered business intelligence pdf: AI-Powered Business Intelligence Tobias Zwingmann, 2022-06-10 Use business intelligence to power corporate growth, increase efficiency, and improve corporate decision making. With this practical book featuring hands-on examples in Power BI with basic Python and R code, you'll explore the most relevant AI use cases for BI, including improved forecasting, automated classification, and AI-powered recommendations. And you'll learn how to draw insights from unstructured data sources like text, document, and image files. Author Tobias Zwingmann helps BI professionals, business analysts, and data analytics understand high-impact areas of artificial intelligence. You'll learn how to leverage popular AI-as-a-service and AutoML platforms to ship enterprise-grade proofs of concept without the help of software engineers or data scientists. Learn how AI can generate business impact in BI environments Use AutoML for automated classification and improved forecasting Implement recommendation services to support decision-making Draw insights from text data at scale with NLP services Extract information from documents and images with computer vision services Build interactive user frontends for AI-powered dashboard prototypes Implement an end-to-end case study for building an AI-powered customer analytics dashboard |
| ai powered business intelligence pdf: AI Meets BI Lakshman Bulusu, Rosendo Abellera, 2020-11-03 With the emergence of Artificial Intelligence (AI) in the business world, a new era of Business Intelligence (BI) has been ushered in to create real-world business solutions using analytics. BI developers and practitioners now have tools and technologies to create systems and solutions to guide effective decision making. Decisions can be made on the basis of more reliable and accurate information and intelligence, which can lead to valuable, actionable insights for business. Previously, BI professionals were stymied by bad or incomplete data, poorly architected solutions, or even just outright incapable systems or resources. With the advent of AI, BI has new possibilities for effectiveness. This is a long-awaited phase for practitioners and developers and, moreover, for executives and leaders relying on knowledgeable and intelligent decision making for their organizations. Beginning with an outline of the traditional methods for implementing BI in the enterprise and how BI has evolved into using self-service analytics, data discovery, and most recently AI, AI Meets BI first lays out the three typical architectures of the first, second, and third generations of BI. It then takes an in-depth look at various types of analytics and highlights how each of these can be implemented using AI-enabled algorithms and deep learning models. The crux of the book is four industry use cases. They describe how an enterprise can access, assess, and perform analytics on data by way of discovering data, defining key metrics that enable the same, defining governance rules, and activating metadata for AI/ML recommendations. Explaining the implementation specifics of each of these four use cases by way of using various AI-enabled machine learning and deep learning algorithms, this book provides complete code for each of the implementations, along with the output of the code, supplemented by visuals that aid in BI-enabled decision making. Concluding with a brief discussion of the cognitive computing aspects of AI, the book looks at future trends, including augmented analytics, automated and autonomous BI, and security and governance of AI-powered BI. |
| ai powered business intelligence pdf: AI and Machine Learning for Coders Laurence Moroney, 2020-10-01 If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics. You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code. You'll learn: How to build models with TensorFlow using skills that employers desire The basics of machine learning by working with code samples How to implement computer vision, including feature detection in images How to use NLP to tokenize and sequence words and sentences Methods for embedding models in Android and iOS How to serve models over the web and in the cloud with TensorFlow Serving |
| ai powered business intelligence pdf: The AI-Powered Workplace Ronald Ashri, 2019-12-09 We are entering the next wave of digital transformation. Artificial intelligence has an ever-increasing significance in our daily lives, and there is no difference when it comes to our workplaces. It is up to you to choose how to utilize these new tools to sharpen your organization’s competitive advantage, improve your team’s well-being, and help your business thrive. In The AI-Powered Workplace, author Ronald Ashri provides a map of the digital landscape to guide you on this timely journey. You’ll understand how the combination of AI, data, and conversational collaboration platforms—such as Slack, Microsoft Teams, and Facebook Workplace—is leading us to a radical shift in how we communicate and solve problems in the modern workplace. Our ability to automate decision-making processes through the application of AI techniques and through modern collaboration tools is a game-changer. Ashri skillfully presents his industry expertise and captivating insights so you have a thorough understanding of how to best combine these technologies with execution strategies that are optimized to your specific needs. The AI-Powered Workplace is an essential technical, cultural, and business handbook that arms you with clear steps to redefine and improve how you get work done. Software is now a proactive workplace partner revolutionizing all aspects of our professional lives from how we collaborate in the digital sphere to the literal physical environments in which we operate our business. This book not only ensures that you do not get left behind, but that you are consistently light years ahead of the pack. What You'll Learn Learn how the introduction of AI-powered applications in the workplace replaces or augments our capabilities and enables activities that were not possible beforeRealize how the combination of AI, data, and messaging platforms (Slack, Microsoft Teams, Skype, WhatsApp) leads to a radical shift in how we communicate, collaborate, and solve problemsDevelop strategies for the digital transformation of organizations through the use of AI-powered applications (from simple chatbots to more complex conversational applications) that operate within messaging environments we use to collaborate with our colleagues dailyKnow the dangers and ethical questions that the introduction of these technologies can cause in the workplace Who This Book is For Professionals at all levels interested in learning how AI, conversational platforms, and data can change organizations, including but not limited to team leaders, managers, and CxOs |
| ai powered business intelligence pdf: Analytics, Data Science, and Artificial Intelligence Ramesh Sharda, Dursun Delen, Efraim Turban, 2020-03-06 For courses in decision support systems, computerized decision-making tools, and management support systems. Market-leading guide to modern analytics, for better business decisionsAnalytics, Data Science, & Artificial Intelligence: Systems for Decision Support is the most comprehensive introduction to technologies collectively called analytics (or business analytics) and the fundamental methods, techniques, and software used to design and develop these systems. Students gain inspiration from examples of organisations that have employed analytics to make decisions, while leveraging the resources of a companion website. With six new chapters, the 11th edition marks a major reorganisation reflecting a new focus -- analytics and its enabling technologies, including AI, machine-learning, robotics, chatbots, and IoT. |
| ai powered business intelligence pdf: The AI-Powered Enterprise Seth Earley, 2020-04-28 Learn how to develop and employ an ontology, the secret weapon for successfully using artificial intelligence to create a powerful competitive advantage in your business. The AI-Powered Enterprise examines two fundamental questions: First, how will the future be different as a result of artificial intelligence? And second, what must companies do to stake their claim on that future? When the Web came along in the mid-90s, it transformed the behavior of customers and remade whole industries. Now, as part of its promise to bring revolutionary change in untold ways to human activity, artificial intelligence--AI--is about to create another complete transformation in how companies create and deliver value to customers. But despite the billions spent so far on bots and other tools, AI continues to stumble. Why can't it magically use all the data organizations generate to make them run faster and better? Because something is missing. AI works only when it understands the soul of the business. An ontology is a holistic digital model of every piece of information that matters to the business, from processes to products to people, and it's what makes the difference between the promise of AI and delivering on that promise. Business leaders who want to catch the AI wave--rather than be crushed by it--need to read The AI-Powered Enterprise. The book is the first to combine a sophisticated explanation of how AI works with a practical approach to applying AI to the problems of business, from customer experience to business operations to product development. |
| ai powered business intelligence pdf: Artificial Intelligence in Banking Introbooks, 2020-04-07 In these highly competitive times and with so many technological advancements, it is impossible for any industry to remain isolated and untouched by innovations. In this era of digital economy, the banking sector cannot exist and operate without the various digital tools offered by the ever new innovations happening in the field of Artificial Intelligence (AI) and its sub-set technologies. New technologies have enabled incredible progression in the finance industry. Artificial Intelligence (AI) and Machine Learning (ML) have provided the investors and customers with more innovative tools, new types of financial products and a new potential for growth.According to Cathy Bessant (the Chief Operations and Technology Officer, Bank of America), AI is not just a technology discussion. It is also a discussion about data and how it is used and protected. She says, In a world focused on using AI in new ways, we're focused on using it wisely and responsibly. |
| ai powered business intelligence pdf: Artificial Intelligence and Machine Learning for Business Steven Finlay, 2018-07 Artificial Intelligence (AI) and Machine Learning are now mainstream business tools. They are being applied across many industries to increase profits, reduce costs, save lives and improve customer experiences. Organizations which understand these tools and know how to use them are benefiting at the expense of their rivals. Artificial Intelligence and Machine Learning for Business cuts through the hype and technical jargon that is often associated with these subjects. It delivers a simple and concise introduction for managers and business people. The focus is very much on practical application and how to work with technical specialists (data scientists) to maximize the benefits of these technologies. This third edition has been substantially revised and updated. It contains several new chapters and covers a broader set of topics than before, but retains the no-nonsense style of the original. |
| ai powered business intelligence pdf: The AI Ladder Rob Thomas, Paul Zikopoulos, 2020-04-30 AI may be the greatest opportunity of our time, with the potential to add nearly $16 trillion to the global economy over the next decade. But so far, adoption has been much slower than anticipated, or so headlines may lead you to believe. With this practical guide, business leaders will discover where they are in their AI journey and learn the steps necessary to successfully scale AI throughout their organization. Authors Rob Thomas and Paul Zikopoulos from IBM introduce C-suite executives and business professionals to the AI Ladder—a unified, prescriptive approach to help them understand and accelerate the AI journey. Complete with real-world examples and real-life experiences, this book explores AI drivers, value, and opportunity, as well as the adoption challenges organizations face. Understand why you can’t have AI without an information architecture (IA) Appreciate how AI is as much a cultural change as it is a technological one Collect data and make it simple and accessible, regardless of where it lives Organize data to create a business-ready analytics foundation Analyze data, and build and scale AI with trust and transparency Infuse AI throughout your entire business and create intelligent workflows |
| ai powered business intelligence pdf: Flow Architectures James Urquhart, 2021-01-06 Software development today is embracing events and streaming data, which optimizes not only how technology interacts but also how businesses integrate with one another to meet customer needs. This phenomenon, called flow, consists of patterns and standards that determine which activity and related data is communicated between parties over the internet. This book explores critical implications of that evolution: What happens when events and data streams help you discover new activity sources to enhance existing businesses or drive new markets? What technologies and architectural patterns can position your company for opportunities enabled by flow? James Urquhart, global field CTO at VMware, guides enterprise architects, software developers, and product managers through the process. Learn the benefits of flow dynamics when businesses, governments, and other institutions integrate via events and data streams Understand the value chain for flow integration through Wardley mapping visualization and promise theory modeling Walk through basic concepts behind today's event-driven systems marketplace Learn how today's integration patterns will influence the real-time events flow in the future Explore why companies should architect and build software today to take advantage of flow in coming years |
| ai powered business intelligence pdf: AI-Powered Business Intelligence for Modern Organizations Natarajan, Arul Kumar, Galety, Mohammad Gouse, Iwendi, Celestine, Das, Deepthi, Shankar, Achyut, 2024-10-01 Technology’s rapid advancement has revolutionized how organizations gather, analyze, and utilize data. In this dynamic landscape, integrating artificial intelligence (AI) into business intelligence (BI) systems has emerged as a critical factor for driving informed decision-making and maintaining competitive advantage. This integration allows business to respond quickly to market changes, personalize customer experiences, and optimize operations with greater precision. As AI-driven BI tools continue to evolve, they empower organizations to harness vast amounts of data more effectively, making strategic decisions that are both timely and data-driven, thereby securing their position in an increasingly competitive marketplace. AI-Powered Business Intelligence for Modern Organizations provides a comprehensive overview of this transformative intersection, addressing the diverse challenges, opportunities, and future trends in this field. By exploring the integration of AI into BI systems, the text delves into how advanced analytics, machine learning, and automation are reshaping the way businesses operate. Covering topics such as augmented analytics, decision-making, and sustainability metrics, this book is an excellent resource for business leaders and executives, data scientists and analysts, IT and technology managers, academicians, researchers, graduate and postgraduate students, consultants, industry experts, and more. |
| ai powered business intelligence pdf: Artificial Intelligence Harvard Business Review, 2019 Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business. |
| ai powered business intelligence pdf: Competing in the Age of AI Marco Iansiti, Karim R. Lakhani, 2020-01-07 a provocative new book — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how collisions between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI. |
| ai powered business intelligence pdf: Business Resilience System (BRS): Driven Through Boolean, Fuzzy Logics and Cloud Computation Bahman Zohuri, Masoud Moghaddam, 2017-02-28 This book provides a technical approach to a Business Resilience System with its Risk Atom and Processing Data Point based on fuzzy logic and cloud computation in real time. Its purpose and objectives define a clear set of expectations for Organizations and Enterprises so their network system and supply chain are totally resilient and protected against cyber-attacks, manmade threats, and natural disasters. These enterprises include financial, organizational, homeland security, and supply chain operations with multi-point manufacturing across the world. Market shares and marketing advantages are expected to result from the implementation of the system. The collected information and defined objectives form the basis to monitor and analyze the data through cloud computation, and will guarantee the success of their survivability's against any unexpected threats. This book will be useful for advanced undergraduate and graduate students in the field of computer engineering, engineers that work for manufacturing companies, business analysts in retail and e-Commerce, and those working in the defense industry, Information Security, and Information Technology. |
| ai powered business intelligence pdf: The Future Computed , 2018 |
| ai powered business intelligence pdf: Innovative Technologies for Market Leadership Patrick Glauner, Philipp Plugmann, 2020-06-11 This book introduces the reader to the latest innovations in fields such as artificial intelligence, systems biology or surgery, and gives advice on what new technologies to consider for becoming a market leader of tomorrow. Companies generally acquire information on these fields from various sources such as market reports, scientific literature or conference events, but find it difficult to distinguish between mere hype and truly valuable innovations. This book offers essential guidance in the form of structured and authoritative contributions by experts in innovative technologies spanning from biology and medicine to augmented reality and smart power grids. The authors identify high-potential fields and demonstrate the impact of their technologies to create economic value in real-world applications. They also offer business leaders advice on whether and how to implement these new technologies and innovations in their companies or businesses. |
| ai powered business intelligence pdf: AI Meets BI Lakshman Bulusu, Rosendo Abellera, 2020-11-03 With the emergence of Artificial Intelligence (AI) in the business world, a new era of Business Intelligence (BI) has been ushered in to create real-world business solutions using analytics. BI developers and practitioners now have tools and technologies to create systems and solutions to guide effective decision making. Decisions can be made on the basis of more reliable and accurate information and intelligence, which can lead to valuable, actionable insights for business. Previously, BI professionals were stymied by bad or incomplete data, poorly architected solutions, or even just outright incapable systems or resources. With the advent of AI, BI has new possibilities for effectiveness. This is a long-awaited phase for practitioners and developers and, moreover, for executives and leaders relying on knowledgeable and intelligent decision making for their organizations. Beginning with an outline of the traditional methods for implementing BI in the enterprise and how BI has evolved into using self-service analytics, data discovery, and most recently AI, AI Meets BI first lays out the three typical architectures of the first, second, and third generations of BI. It then takes an in-depth look at various types of analytics and highlights how each of these can be implemented using AI-enabled algorithms and deep learning models. The crux of the book is four industry use cases. They describe how an enterprise can access, assess, and perform analytics on data by way of discovering data, defining key metrics that enable the same, defining governance rules, and activating metadata for AI/ML recommendations. Explaining the implementation specifics of each of these four use cases by way of using various AI-enabled machine learning and deep learning algorithms, this book provides complete code for each of the implementations, along with the output of the code, supplemented by visuals that aid in BI-enabled decision making. Concluding with a brief discussion of the cognitive computing aspects of AI, the book looks at future trends, including augmented analytics, automated and autonomous BI, and security and governance of AI-powered BI. |
| ai powered business intelligence pdf: AI in the Wild Peter Dauvergne, 2020-09-15 Examining the potential benefits and risks of using artificial intelligence to advance global sustainability. Drones with night vision are tracking elephant and rhino poachers in African wildlife parks and sanctuaries; smart submersibles are saving coral from carnivorous starfish on Australia's Great Barrier Reef; recycled cell phones alert Brazilian forest rangers to the sound of illegal logging. The tools of artificial intelligence are being increasingly deployed in the battle for global sustainability. And yet, warns Peter Dauvergne, we should be cautious in declaring AI the planet's savior. In AI in the Wild, Dauvergne avoids the AI industry-powered hype and offers a critical view, exploring both the potential benefits and risks of using artificial intelligence to advance global sustainability. |
| ai powered business intelligence pdf: The Economics of Artificial Intelligence Ajay Agrawal, Joshua Gans, Avi Goldfarb, Catherine Tucker, 2024-03-05 A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system. |
| ai powered business intelligence pdf: Digital Entrepreneurship Mariusz Soltanifar, Mathew Hughes, Lutz Göcke, 2020-11-13 This open access book explores the global challenges and experiences related to digital entrepreneurial activities, using carefully selected examples from leading companies and economies that shape world business today and tomorrow. Digital entrepreneurship and the companies steering it have an enormous global impact; they promise to transform the business world and change the way we communicate with each other. These companies use digitalization and artificial intelligence to enhance the quality of decisions and augment their business and customer operations. This book demonstrates how cloud services are continuing to evolve; how cryptocurrencies are traded in the banking industry; how platforms are created to commercialize business, and how, taken together, these developments provide new opportunities in the digitalized era. Further, it discusses a wide range of digital factors changing the way businesses operate, including artificial intelligence, chatbots, voice search, augmented and virtual reality, as well as cyber threats and data privacy management. “Digitalization mirrors the Industrial Revolution’s impact. This book provides a complement of perspectives on the opportunities emanating from such a deep seated change in our economy. It is a comprehensive collection of thought leadership mapped into a very useful framework. Scholars, digital entrepreneurs and practitioners will benefit from this timely work.” Gina O’Connor, Professor of Innovation Management at Babson College, USA “This book defines and delineates the requirements for companies to enable their businesses to succeed in a post-COVID19 world. This book deftly examines how to accomplish and achieve digital entrepreneurship by leveraging cloud computing, AI, IoT and other critical technologies. This is truly a unique “must-read” book because it goes beyond theory and provides practical examples.” Charlie Isaacs, CTO of Customer Connection at Salesforce.com, USA This book provides digital entrepreneurs useful guidance identifying, validating and building their venture. The international authors developed new perspectives on digital entrepreneurship that can support to create impact ventures.” Felix Staeritz, CEO FoundersLane, Member of the World Economic Forum Digital Leaders Board and bestselling author of FightBack, Germany |
| ai powered business intelligence pdf: Artificial Intelligence for Business Hemachandran K, Raul V. Rodriguez, 2023-11-21 Artificial intelligence (AI) is transforming the business world at an unprecedented pace. From automating mundane tasks to predicting consumer behaviour, AI is changing the way businesses operate across all sectors. This book is an exploration of AI in business applications, highlighting the diverse range of ways in which AI is being used across different industries. The book begins with an overview of AI in business and its impact on the workforce. It then explores the role of AI in marketing, advertising, and tourism. The use of AI in personalized recommendations and chatbots is discussed in detail. The book then moves on to examine how AI is changing the retail industry, improving supply chain management, and enhancing the customer experience. The media and entertainment industry is also examined, with a focus on how AI is being used to personalize content and improve the user experience. The book also explores the use of AI in human resources, insurance, legal, and finance. The impact of AI on talent identification, recruitment, underwriting, document analysis, and financial forecasting is discussed in detail. In the healthcare and sports industries, AI is transforming the way we approach diagnosis, treatment, and training. The book examines how AI is being used to analyse medical images, develop personalized treatment plans, and improve patient outcomes. The use of AI in sports performance analysis is also discussed in detail. Finally, the book explores the use of AI in agriculture, energy, education, and the public sector. The potential of AI to optimize crop yields, reduce energy consumption, and improve the quality of education is discussed in detail. The book also examines how AI is being used to improve public services, such as transportation and emergency services. This book is a valuable resource for academics, researchers, professionals, and policymakers who are interested in understanding the potential of AI in the business world. The contributions from leading experts and researchers provide a comprehensive overview of AI in business applications, and how it is transforming different sectors. The book also examines the ethical dilemmas that arise from the use of AI in business, such as the impact on privacy and data security, and the potential for bias in AI algorithms. It provides valuable insights into how businesses can ensure that the use of AI is ethical and responsible. In conclusion, this book is a must-read for anyone interested in the potential of AI in the business world. It provides a comprehensive overview of AI in business applications and how it is transforming different sectors. The book examines the ethical dilemmas that arise from the use of AI in business, providing valuable insights into how businesses can ensure that the use of AI is ethical and responsible. We hope that readers will find this book informative and thought-provoking. |
| ai powered business intelligence pdf: AI and Big Data on IBM Power Systems Servers Scott Vetter, Ivaylo B. Bozhinov, Anto A John, Rafael Freitas de Lima, Ahmed.(Mash) Mashhour, James Van Oosten, Fernando Vermelho, Allison White, IBM Redbooks, 2019-04-10 As big data becomes more ubiquitous, businesses are wondering how they can best leverage it to gain insight into their most important business questions. Using machine learning (ML) and deep learning (DL) in big data environments can identify historical patterns and build artificial intelligence (AI) models that can help businesses to improve customer experience, add services and offerings, identify new revenue streams or lines of business (LOBs), and optimize business or manufacturing operations. The power of AI for predictive analytics is being harnessed across all industries, so it is important that businesses familiarize themselves with all of the tools and techniques that are available for integration with their data lake environments. In this IBM® Redbooks® publication, we cover the best practices for deploying and integrating some of the best AI solutions on the market, including: IBM Watson Machine Learning Accelerator (see note for product naming) IBM Watson Studio Local IBM Power SystemsTM IBM SpectrumTM Scale IBM Data Science Experience (IBM DSX) IBM Elastic StorageTM Server Hortonworks Data Platform (HDP) Hortonworks DataFlow (HDF) H2O Driverless AI We map out all the integrations that are possible with our different AI solutions and how they can integrate with your existing or new data lake. We also walk you through some of our client use cases and show you how some of the industry leaders are using Hortonworks, IBM PowerAI, and IBM Watson Studio Local to drive decision making. We also advise you on your deployment options, when to use a GPU, and why you should use the IBM Elastic Storage Server (IBM ESS) to improve storage management. Lastly, we describe how to integrate IBM Watson Machine Learning Accelerator and Hortonworks with or without IBM Watson Studio Local, how to access real-time data, and security. Note: IBM Watson Machine Learning Accelerator is the new product name for IBM PowerAI Enterprise. Note: Hortonworks merged with Cloudera in January 2019. The new company is called Cloudera. References to Hortonworks as a business entity in this publication are now referring to the merged company. Product names beginning with Hortonworks continue to be marketed and sold under their original names. |
| ai powered business intelligence pdf: Data Warehouse Barry Devlin, 1997 Data warehousing is one of the hottest topics in the computing industry. Written by Barry Devlin, one of the world's leading experts on data warehousing, this book gives you the insights and experiences gained over 10 years and offers the most comprehensive, practical guide to designing, building, and implementing a successful data warehouse. Included in this vital information is an explanation of the optimal three-tiered architecture for the data warehouse, with a clear division between data and information. Information systems managers will appreciate the full description of the functions needed to implement such an architecture, including reconciling existing, diverse data and deriving consistent, valuable business information. |
| ai powered business intelligence pdf: The AI Book Ivana Bartoletti, Anne Leslie, Shân M. Millie, 2020-06-29 Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important |
| ai powered business intelligence pdf: Artificial Intelligence in Practice Bernard Marr, 2019-04-15 Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce. |
| ai powered business intelligence pdf: Artificial Intelligence for Marketing Jim Sterne, 2017-08-14 A straightforward, non-technical guide to the next major marketing tool Artificial Intelligence for Marketing presents a tightly-focused introduction to machine learning, written specifically for marketing professionals. This book will not teach you to be a data scientist—but it does explain how Artificial Intelligence and Machine Learning will revolutionize your company's marketing strategy, and teach you how to use it most effectively. Data and analytics have become table stakes in modern marketing, but the field is ever-evolving with data scientists continually developing new algorithms—where does that leave you? How can marketers use the latest data science developments to their advantage? This book walks you through the need-to-know aspects of Artificial Intelligence, including natural language processing, speech recognition, and the power of Machine Learning to show you how to make the most of this technology in a practical, tactical way. Simple illustrations clarify complex concepts, and case studies show how real-world companies are taking the next leap forward. Straightforward, pragmatic, and with no math required, this book will help you: Speak intelligently about Artificial Intelligence and its advantages in marketing Understand how marketers without a Data Science degree can make use of machine learning technology Collaborate with data scientists as a subject matter expert to help develop focused-use applications Help your company gain a competitive advantage by leveraging leading-edge technology in marketing Marketing and data science are two fast-moving, turbulent spheres that often intersect; that intersection is where marketing professionals pick up the tools and methods to move their company forward. Artificial Intelligence and Machine Learning provide a data-driven basis for more robust and intensely-targeted marketing strategies—and companies that effectively utilize these latest tools will reap the benefit in the marketplace. Artificial Intelligence for Marketing provides a nontechnical crash course to help you stay ahead of the curve. |
| ai powered business intelligence pdf: Artificial Intelligence And International Politics Valerie M Hudson, 2019-08-30 For well over a decade researchers in international relations have sought ways to combine the rigor of quantitative techniques with the richness of qualitative data. Many have discovered that artificial intelligence computer models allow them to do just that. Computer programs modeling international interactions and foreign policy decision making attempt to reflect such human characteristics as learning, memory, and adaptation. In this volume of original essays, distinguished scholars present a comprehensive overview of their research and reflect on the potential of artificial intelligence as a tool for furthering our understanding of international affairs. The contributors take a broad look at the early stirrings of interest in artificial intelligence as a potentially useful method of political analysis, exploring such topics as intentionality, time sense, and knowledge representation. The work also focuses on the current state of artificial intelligence and examines its general areas of emphasis: international interaction, decision making groups, and cognitive processes in international politics. The contributors represent a cross section of different approaches to using artificial intelligence and reflect the major research programs across the country in this new international relations subfield |
| ai powered business intelligence pdf: Artificial Intelligence for Business Rajendra Akerkar, 2018-08-11 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. |
| ai powered business intelligence pdf: Enterprise Artificial Intelligence Transformation Rashed Haq, 2020-06-10 Enterprise Artificial Intelligence Transformation AI is everywhere. From doctor's offices to cars and even refrigerators, AI technology is quickly infiltrating our daily lives. AI has the ability to transform simple tasks into technological feats at a human level. This will change the world, plain and simple. That's why AI mastery is such a sought-after skill for tech professionals. Author Rashed Haq is a subject matter expert on AI, having developed AI and data science strategies, platforms, and applications for Publicis Sapient's clients for over 10 years. He shares that expertise in the new book, Enterprise Artificial Intelligence Transformation. The first of its kind, this book grants technology leaders the insight to create and scale their AI capabilities and bring their companies into the new generation of technology. As AI continues to grow into a necessary feature for many businesses, more and more leaders are interested in harnessing the technology within their own organizations. In this new book, leaders will learn to master AI fundamentals, grow their career opportunities, and gain confidence in machine learning. Enterprise Artificial Intelligence Transformation covers a wide range of topics, including: Real-world AI use cases and examples Machine learning, deep learning, and slimantic modeling Risk management of AI models AI strategies for development and expansion AI Center of Excellence creating and management If you're an industry, business, or technology professional that wants to attain the skills needed to grow your machine learning capabilities and effectively scale the work you're already doing, you'll find what you need in Enterprise Artificial Intelligence Transformation. |
| ai powered business intelligence pdf: Artificial Intelligence Illuminated Ben Coppin, 2004 Artificial Intelligence Illuminated presents an overview of the background and history of artificial intelligence, emphasizing its importance in today's society and potential for the future. The book covers a range of AI techniques, algorithms, and methodologies, including game playing, intelligent agents, machine learning, genetic algorithms, and Artificial Life. Material is presented in a lively and accessible manner and the author focuses on explaining how AI techniques relate to and are derived from natural systems, such as the human brain and evolution, and explaining how the artificial equivalents are used in the real world. Each chapter includes student exercises and review questions, and a detailed glossary at the end of the book defines important terms and concepts highlighted throughout the text. |
| ai powered business intelligence pdf: A Model to Forecast Future Paradigms Bahman Zohuri, Farhang Mossavar-Rahmani, 2020 In this volume, A Model to Forecast Future Paradigms, Volume 1: Introduction to Knowledge Is Power in Four Dimensions, the authors' two-fold objective is to lay out a methodology and approach that allows the reader to learn how to utilize existing technology in the form of computer software and hardware for forecasting and decision-making and to discuss factors that affect upcoming events that, in turn, shape future paradigms. The book provides an understanding of these factors that will help decision-makers be better prepared to face future challenges and will assist them coping with unexpected circumstances. This volume is divided into two parts. Part one discusses a technological infrastructure so that new readers can gain a greater understanding based on the knowledge of tomorrow's computing functionality. The second part goes on to discuss the key indicators in the areas of population, culture, economics, climate change, and the impacts of technology in commerce and socially--which all need to be considered when forecasting a future paradigm. |
| ai powered business intelligence pdf: Business Analytics for Managers Gert Laursen, Jesper Thorlund, 2010-07-13 While business analytics sounds like a complex subject, this book provides a clear and non-intimidating overview of the topic. Following its advice will ensure that your organization knows the analytics it needs to succeed, and uses them in the service of key strategies and business processes. You too can go beyond reporting!—Thomas H. Davenport, President's Distinguished Professor of IT and Management, Babson College; coauthor, Analytics at Work: Smarter Decisions, Better Results Deliver the right decision support to the right people at the right time Filled with examples and forward-thinking guidance from renowned BA leaders Gert Laursen and Jesper Thorlund, Business Analytics for Managers offers powerful techniques for making increasingly advanced use of information in order to survive any market conditions. Take a look inside and find: Proven guidance on developing an information strategy Tips for supporting your company's ability to innovate in the future by using analytics Practical insights for planning and implementing BA How to use information as a strategic asset Why BA is the next stepping-stone for companies in the information age today Discussion on BA's ever-increasing role Improve your business's decision making. Align your business processes with your business's objectives. Drive your company into a prosperous future. Taking BA from buzzword to enormous value-maker, Business Analytics for Managers helps you do it all with workable solutions that will add tremendous value to your business. |
| ai powered business intelligence pdf: Handbook on Decision Support Systems 2 Frada Burstein, Clyde W. Holsapple, 2008-01-22 As the most comprehensive reference work dealing with decision support systems (DSS), this book is essential for the library of every DSS practitioner, researcher, and educator. Written by an international array of DSS luminaries, it contains more than 70 chapters that approach decision support systems from a wide variety of perspectives. These range from classic foundations to cutting-edge thought, informative to provocative, theoretical to practical, historical to futuristic, human to technological, and operational to strategic. The chapters are conveniently organized into ten major sections that novices and experts alike will refer to for years to come. |
| ai powered business intelligence pdf: Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance El Bachir Boukherouaa, Mr. Ghiath Shabsigh, Khaled AlAjmi, Jose Deodoro, Aquiles Farias, Ebru S Iskender, Mr. Alin T Mirestean, Rangachary Ravikumar, 2021-10-22 This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight. |
| ai powered business intelligence pdf: Business Intelligence David Loshin, 2012-11-27 Business Intelligence: The Savvy Managers Guide, Second Edition, discusses the objectives and practices for designing and deploying a business intelligence (BI) program. It looks at the basics of a BI program, from the value of information and the mechanics of planning for success to data model infrastructure, data preparation, data analysis, integration, knowledge discovery, and the actual use of discovered knowledge. Organized into 21 chapters, this book begins with an overview of the kind of knowledge that can be exposed and exploited through the use of BI. It then proceeds with a discussion of information use in the context of how value is created within an organization, how BI can improve the ways of doing business, and organizational preparedness for exploiting the results of a BI program. It also looks at some of the critical factors to be taken into account in the planning and execution of a successful BI program. In addition, the reader is introduced to considerations for developing the BI roadmap, the platforms for analysis such as data warehouses, and the concepts of business metadata. Other chapters focus on data preparation and data discovery, the business rules approach, and data mining techniques and predictive analytics. Finally, emerging technologies such as text analytics and sentiment analysis are considered. This book will be valuable to data management and BI professionals, including senior and middle-level managers, Chief Information Officers and Chief Data Officers, senior business executives and business staff members, database or software engineers, and business analysts. - Guides managers through developing, administering, or simply understanding business intelligence technology - Keeps pace with the changes in best practices, tools, methods and processes used to transform an organization's data into actionable knowledge - Contains a handy, quick-reference to technologies and terminology |
| ai powered business intelligence pdf: Artificial Intelligence in Healthcare Adam Bohr, Kaveh Memarzadeh, 2020-06-21 Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data |
| ai powered business intelligence pdf: WIPO Technology Trends 2019 - Artificial Intelligence World Intellectual Property Organization, 2019-01-21 The first report in a new flagship series, WIPO Technology Trends, aims to shed light on the trends in innovation in artificial intelligence since the field first developed in the 1950s. |
| ai powered business intelligence pdf: AI-Powered IoT for COVID-19 Fadi Al-Turjman, 2020-12-10 The Internet of Things (IoT) has made revolutionary advances in the utility grid as we know it. Among these advances, intelligent medical services are gaining much interest. The use of Artificial Intelligence (AI) is increasing day after day in fighting one of the most significant viruses, COVID-19. The purpose of this book is to present the detailed recent exploration of AI and IoT in the COVID-19 pandemic and similar applications. The integrated AI and IoT paradigm is widely used in most medical applications, as well as in sectors that deal with transacting data every day. This book can be used by computer science undergraduate and postgraduate students; researchers and practitioners; and city administrators, policy makers, and government regulators. It presents a smart and up-to-date model for COVID-19 and similar applications. Novel architectural and medical use cases in the smart city project are the core aspects of this book. The wide variety of topics it presents offers readers multiple perspectives on a variety of disciplines. Prof. Dr. Fadi Al-Turjman received his PhD in computer science from Queen’s University, Kingston, Ontario, Canada, in 2011. He is a full professor and research center director at Near East University, Nicosia, Cyprus. |
| ai powered business intelligence pdf: Artificial Intelligence in Education Matthew N.O. Sadiku, Sarhan M. Musa, Uwakwe C. Chukwu, 2022-01-27 The quest for building an artificial brain developed in the fields of computer science and psychology. Artificial intelligence (AI), sometimes called machine intelligence, refers to intelligence demonstrated by machines, while the natural intelligence is the intelligence displayed by humans and animals. Typically, AI systems demonstrate at least some of the following human behaviors: planning, learning, reasoning, problem solving, knowledge representation, perception, speech recognition, decision-making, language translation, motion, manipulation, intelligence, and creativity. Artificial intelligence is an emerging technology which the educational sector can benefit from. In this book, we consider the applications of AI in key areas of education. Artificial intelligence in education (AIED) refers to the application of AI technologies in educational settings to facilitate teaching, learning, or decision making. AI will impact the education field in the areas of administration, instruction, and personalized, and individualized learning applications. In this book, AI is specifically applied in the following key educational sectors: education, natural sciences, social sciences, computer science, engineering, business, and medicine. |
| ai powered business intelligence pdf: An Introduction to Data Francesco Corea, 2018-11-27 This book reflects the author’s years of hands-on experience as an academic and practitioner. It is primarily intended for executives, managers and practitioners who want to redefine the way they think about artificial intelligence (AI) and other exponential technologies. Accordingly the book, which is structured as a collection of largely self-contained articles, includes both general strategic reflections and detailed sector-specific information. More concretely, it shares insights into what it means to work with AI and how to do it more efficiently; what it means to hire a data scientist and what new roles there are in the field; how to use AI in specific industries such as finance or insurance; how AI interacts with other technologies such as blockchain; and, in closing, a review of the use of AI in venture capital, as well as a snapshot of acceleration programs for AI companies. |
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ISO - What is artificial intelligence (AI)?
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