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| automation in business intelligence: INTELLIGENT AUTOMATION PASCAL. BARKIN BORNET (IAN. WIRTZ, JOCHEN.), 2020 |
| automation in business intelligence: The Biml Book Andy Leonard, Scott Currie, Jacob Alley, Martin Andersson, Peter Avenant, Bill Fellows, Simon Peck, Reeves Smith, Raymond Sondak, Benjamin Weissman, Cathrine Wilhelmsen, 2017-10-30 Learn Business Intelligence Markup Language (Biml) for automating much of the repetitive, manual labor involved in data integration. We teach you how to build frameworks and use advanced Biml features to get more out of SQL Server Integration Services (SSIS), Transact-SQL (T-SQL), and SQL Server Analysis Services (SSAS) than you ever thought possible. The first part of the book starts with the basics—getting your development environment configured, Biml syntax, and scripting essentials. Whether a beginner or a seasoned Biml expert, the next part of the book guides you through the process of using Biml to build a framework that captures both your design patterns and execution management. Design patterns are reusable code blocks that standardize the approach you use to perform certain types of data integration, logging, and other key data functions. Design patterns solve common problems encountered when developing data integration solutions. Because you do not have to build the code from scratch each time, design patterns improve your efficiency as a Biml developer. In addition to leveraging design patterns in your framework, you will learn how to build a robust metadata store and how to package your framework into Biml bundles for deployment within your enterprise. In the last part of the book, we teach you more advanced Biml features and capabilities, such as SSAS development, T-SQL recipes, documentation autogeneration, and Biml troubleshooting. The Biml Book: Provides practical and applicable examples Teaches you how to use Biml to reduce development time while improving quality Takes you through solutions to common data integration and BI challenges What You'll Learn Master the basics of Business Intelligence Markup Language (Biml) Study patterns for automating SSIS package generation Build a Biml Framework Import and transform database schemas Automate generation of scripts and projects Who This Book Is For BI developers wishing to quickly locate previously tested solutions, Microsoft BI specialists, those seeking more information about solution automation and code generation, and practitioners of Data Integration Lifecycle Management (DILM) in the DevOps enterprise |
| automation in business intelligence: 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. |
| automation in business intelligence: INTELLIGENT AUTOMATION Pascal Bornet, 2020-10-14 TESTIMONIALS “One of the most important books of our times!” – Bernard Marr “An essential reading for anybody who cares about the future of work” – Arianna Huffington This insightful and practical guidebook is instrumental for success in the Fourth Industrial Revolution” – Klaus Schwab, founder of the World Economic Forum “An insightful exploration of Intelligent Automation” – Dr. Kai-Fu Lee, Author of NYT Bestseller AI Superpowers “This field guide is essential reading” – Gartner “Masterful insight, this book is more relevant than ever” – HFS “This book needed to be written” – Forrester ABOUT THE BOOK This is the first book on Intelligent Automation (IA). Also called Hyperautomation, it is one of the most recent trends in the field of artificial intelligence. IA is a cutting-edge combination of methods and technologies, involving people, organizations, machine learning, low-code platforms, robotic process automation (RPA), and more. This book is for everyone – whether you are an experienced practitioner, new to the topic, or simply interested in what the future holds for enterprises, work, life, and society as a whole. Key content of the book: > What is Intelligent Automation (IA)? Why has the use of IA been expanding so rapidly? What are the benefits it unleashes for employees, companies, customers, and society? > How have leading organizations been able to harness the full potential of IA, at scale, and generate massive efficiency gains in the range of 20 to 60%? > How can IA save 10+ million lives per year, triple our global budget for education, eliminate hunger, help protect our planet, or increase the resilience of society to pandemics and crises? What you will get from this book: > Get the lessons learned from 100+ IA transformation successes (and failures) > Benefit from the largest publicly available library of 500+ IA use cases by industry and by business function > Gain access to insights garnered from 200+ IA industry experts Read more about this book: www.intelligentautomationbook.com and get it on Amazon: https://www.amazon.fr/dp/B08KFLY51Y WHY THIS BOOK? While many books have been published on AI, machine learning, or robotics, a comprehensive reference guidebook had never yet been written on the topic of IA. Also, it seemed essential to us to work towards establishing IA as a field, with its own frameworks, use cases, methods, and critical success factors. ABOUT THE AUTHORS Pascal Bornet is a recognized global expert, thought leader, and pioneer in the field of intelligent automation (IA). He founded and led the IA practices for Mckinsey & Company and Ernst & Young (EY), where he drove hundreds of IA transformations across industries. Bornet is a member of the Forbes Technology Council, and he was awarded Global Top Voice in Technology 2019. lan Barkin is Chief Strategy & Marketing Officer at SYKES. He is a globally recognized thought leader and veteran in the IA space. Barkin co-founded Symphony Ventures, a pure-play IA consulting company providing cutting-edge services across all sectors. In 2018, the company was acquired for US$69 million by SYKES, a NASDAQ-listed global leader. Dr. Jochen Wirtz is Vice-Dean MBA Programmes at the National University of Singapore Business School, and Professor of Marketing. He is a well-known and highly acclaimed author with more than 20 books published, including Services Marketing - People, Technology, Strategy. His research has been published in over 100 academic journal articles, and he received over 40 awards. |
| automation in business intelligence: Business Intelligence Tools for Small Companies Albert Nogués, Juan Valladares, 2017-05-25 Learn how to transition from Excel-based business intelligence (BI) analysis to enterprise stacks of open-source BI tools. Select and implement the best free and freemium open-source BI tools for your company’s needs and design, implement, and integrate BI automation across the full stack using agile methodologies. Business Intelligence Tools for Small Companies provides hands-on demonstrations of open-source tools suitable for the BI requirements of small businesses. The authors draw on their deep experience as BI consultants, developers, and administrators to guide you through the extract-transform-load/data warehousing (ETL/DWH) sequence of extracting data from an enterprise resource planning (ERP) database freely available on the Internet, transforming the data, manipulating them, and loading them into a relational database. The authors demonstrate how to extract, report, and dashboard key performance indicators (KPIs) in a visually appealing format from the relational database management system (RDBMS). They model the selection and implementation of free and freemium tools such as Pentaho Data Integrator and Talend for ELT, Oracle XE and MySQL/MariaDB for RDBMS, and Qliksense, Power BI, and MicroStrategy Desktop for reporting. This richly illustrated guide models the deployment of a small company BI stack on an inexpensive cloud platform such as AWS. What You'll Learn You will learn how to manage, integrate, and automate the processes of BI by selecting and implementing tools to: Implement and manage the business intelligence/data warehousing (BI/DWH) infrastructure Extract data from any enterprise resource planning (ERP) tool Process and integrate BI data using open-source extract-transform-load (ETL) tools Query, report, and analyze BI data using open-source visualization and dashboard tools Use a MOLAP tool to define next year's budget, integrating real data with target scenarios Deploy BI solutions and big data experiments inexpensively on cloud platforms Who This Book Is For Engineers, DBAs, analysts, consultants, and managers at small companies with limited resources but whose BI requirements have outgrown the limitations of Excel spreadsheets; personnel in mid-sized companies with established BI systems who are exploring technological updates and more cost-efficient solutions |
| automation in business intelligence: The Executive's How-To Guide to Automation George E. Danner, 2018-12-17 From driverless cars to pilotless planes, many functions that have previously required human labor can now be performed using artificial intelligence. For businesses, this use of AI results in reduced labor costs and, even more important, creating a competitive advantage. How does one look at any organization and begin the work of automating it in sensible ways? This book provides the blueprint for automating critical business functions of all kinds. It outlines the skills and technologies that must be brought to bear on replicating human-like thinking and judgment in the form of algorithms. Many believe that algorithm design is the exclusive purview of computer scientists and experienced programmers. This book aims to dispel that notion. An algorithm is merely a set of rules, and anyone with the ability to envision how different components of a business can interact with other components already has the ability to work in algorithms. Though many fear that the use of automation in business means human labor will no longer be needed, the author argues that organizations will re-purpose humans into different roles under the banner of automation, not simply get rid of them. He also identifies parts of business that are best targeted for automation. This book will arm business people with the tools needed to automate companies, making them perform better, move faster, operate cheaper, and provide great lasting value to investors. |
| automation in business intelligence: 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. |
| automation in business intelligence: Internet of Things in Business Transformation Parul Gandhi, Surbhi Bhatia, Abhishek Kumar, Mohammad Ali Alojail, Pramod Singh Rathore, 2021-02-03 The objective of this book is to teach what IoT is, how it works, and how it can be successfully utilized in business. This book helps to develop and implement a powerful IoT strategy for business transformation as well as project execution. Digital change, business creation/change and upgrades in the ways and manners in which we work, live, and engage with our clients and customers, are all enveloped by the Internet of Things which is now named Industry 5.0 or Industrial Internet of Things. The sheer number of IoT(a billion+), demonstrates the advent of an advanced business society led by sustainable robotics and business intelligence. This book will be an indispensable asset in helping businesses to understand the new technology and thrive. |
| automation in business intelligence: The Automation Advantage: Embrace the Future of Productivity and Improve Speed, Quality, and Customer Experience Through AI Bhaskar Ghosh, Rajendra Prasad, Gayathri Pallail, 2021-12-07 From the global automation leaders at Accenture—the first-ever comprehensive blueprint for how to use and scale AI-powered intelligent automation in the enterprise to gain competitive advantage through faster speed to market, improved product quality, higher efficiency, and an elevated customer experience. Many companies were already implementing limited levels of automation when the pandemic hit. But the need to rapidly change business processes and how organizations work resulted in the compression of a decade’s worth of digital transformation into a matter of months. Technology suddenly became the essential element for rapid organizational change and the creation of 360-degree value benefiting all stakeholders. Businesses are faced with the imperative to embrace that change or risk being left behind. In The Automation Advantage, global enterprise technology and automation veterans Bhaskar Ghosh, Rajendra Prasad, and Gayathri Pallail give business leaders and managers the action plan they need to execute a strategic agenda that enables them to quickly and confidently scale their automation and AI initiatives. This practical and highly accessible implementation guide answers leaders’ burning questions, such as: How do I identify and prioritize automation opportunities? How do I assess my legacy systems and data issues? How do I derive full value out of my technology investments and automation efforts? How can I inspire my employees to embrace change and the new opportunities presented by automation? The Automation Advantage goes beyond optimizing process to using AI to transform almost any business activity in any industry to make it faster, more streamlined, cost efficient, and customer-focused—vastly improving overall productivity and performance. Featuring case studies of successful automation solutions, this indispensable road map includes guiding principles for technology, governance, culture, and leadership change. It offers a human-centric approach to AI and automation that leads to sustainable transformation and measurable business results. |
| automation in business intelligence: Business Intelligence Jerzy Surma, 2011-03-06 This book is about using business intelligence as a management information system for supporting managerial decision making. It concentrates primarily on practical business issues and demonstrates how to apply data warehousing and data analytics to support business decision making. This book progresses through a logical sequence, starting with data model infrastructure, then data preparation, followed by data analysis, integration, knowledge discovery, and finally the actual use of discovered knowledge. All examples are based on the most recent achievements in business intelligence. Finally this book outlines an overview of a methodology that takes into account the complexity of developing applications in an integrated business intelligence environment. This book is written for managers, business consultants, and undergraduate and postgraduates students in business administration. |
| automation in business intelligence: Business Intelligence Marinela Mircea, 2012-02-01 The work addresses to specialists in informatics, with preoccupations in development of Business Intelligence systems, and also to beneficiaries of such systems, constituting an important scientific contribution. Experts in the field contribute with new ideas and concepts regarding the development of Business Intelligence applications and their adoption in organizations. This book presents both an overview of Business Intelligence and an in-depth analysis of current applications and future directions for this technology. The book covers a large area, including methods, concepts, and case studies related to: constructing an enterprise business intelligence maturity model, developing an agile architecture framework that leverages the strengths of business intelligence, decision management and service orientation, adding semantics to Business Intelligence, towards business intelligence over unified structured and unstructured data using XML, density-based clustering and anomaly detection, data mining based on neural networks. |
| automation in business intelligence: Hyperautomation Matt Calkins, Neil Ward-Dutton, George Westerman, Lakshmi N, Sidney Fernandes, Alice Wei, Chris Skinner, Isaac Sacolick, John Rymer, Lisa Heneghan, Darren Blake, Rob Galbraith, Ron Tolido, Michael Beckley, 2020-11-20 HYPERAUTOMATION is a collection of expert essays on low-code development and the future of business process automation. In each chapter, an academic, analyst, implementer, or end-user examines different aspects of low-code and automation in the enterprise, clarifying both value and barriers through personal experiences and insights. With contributions from: Dr. George Westerman, MIT - Neil Ward-Dutton, IDC - Lakshmi N, Tata Consultancy Services - Sidney Fernandes & Alice Wei, University of South Florida - Lisa Heneghan, KPMG - Chris Skinner, FinTech expert - John R. Rymer, Forrester (Emeritus) - Isaac Sacolick, StarCIO - Darren Blake, Bexley Neighbourhood Care - Rob Galbraith, InsureTech expert - Ron Tolido, Capgemini - Michael Beckley, Appian All proceeds from the sale of this book will be donated to Black Girls Code, an organization providing young girls of color opportunities to learn in-demand skills in technology and computer programming. |
| automation in business intelligence: Agile Analytics Ken Collier, 2012 Using Agile methods, you can bring far greater innovation, value, and quality to any data warehousing (DW), business intelligence (BI), or analytics project. However, conventional Agile methods must be carefully adapted to address the unique characteristics of DW/BI projects. In Agile Analytics, Agile pioneer Ken Collier shows how to do just that. Collier introduces platform-agnostic Agile solutions for integrating infrastructures consisting of diverse operational, legacy, and specialty systems that mix commercial and custom code. Using working examples, he shows how to manage analytics development teams with widely diverse skill sets and how to support enormous and fast-growing data volumes. Collier's techniques offer optimal value whether your projects involve back-end data management, front-end business analysis, or both. Part I focuses on Agile project management techniques and delivery team coordination, introducing core practices that shape the way your Agile DW/BI project community can collaborate toward success Part II presents technical methods for enabling continuous delivery of business value at production-quality levels, including evolving superior designs; test-driven DW development; version control; and project automation Collier brings together proven solutions you can apply right now--whether you're an IT decision-maker, data warehouse professional, database administrator, business intelligence specialist, or database developer. With his help, you can mitigate project risk, improve business alignment, achieve better results--and have fun along the way. |
| automation in business intelligence: Automating Open Source Intelligence Robert Layton, Paul A Watters, 2015-12-03 Algorithms for Automating Open Source Intelligence (OSINT) presents information on the gathering of information and extraction of actionable intelligence from openly available sources, including news broadcasts, public repositories, and more recently, social media. As OSINT has applications in crime fighting, state-based intelligence, and social research, this book provides recent advances in text mining, web crawling, and other algorithms that have led to advances in methods that can largely automate this process. The book is beneficial to both practitioners and academic researchers, with discussions of the latest advances in applications, a coherent set of methods and processes for automating OSINT, and interdisciplinary perspectives on the key problems identified within each discipline. Drawing upon years of practical experience and using numerous examples, editors Robert Layton, Paul Watters, and a distinguished list of contributors discuss Evidence Accumulation Strategies for OSINT, Named Entity Resolution in Social Media, Analyzing Social Media Campaigns for Group Size Estimation, Surveys and qualitative techniques in OSINT, and Geospatial reasoning of open data. - Presents a coherent set of methods and processes for automating OSINT - Focuses on algorithms and applications allowing the practitioner to get up and running quickly - Includes fully developed case studies on the digital underground and predicting crime through OSINT - Discusses the ethical considerations when using publicly available online data |
| automation in business intelligence: Integration Challenges for Analytics, Business Intelligence, and Data Mining Azevedo, Ana, Santos, Manuel Filipe, 2020-12-11 As technology continues to advance, it is critical for businesses to implement systems that can support the transformation of data into information that is crucial for the success of the company. Without the integration of data (both structured and unstructured) mining in business intelligence systems, invaluable knowledge is lost. However, there are currently many different models and approaches that must be explored to determine the best method of integration. Integration Challenges for Analytics, Business Intelligence, and Data Mining is a relevant academic book that provides empirical research findings on increasing the understanding of using data mining in the context of business intelligence and analytics systems. Covering topics that include big data, artificial intelligence, and decision making, this book is an ideal reference source for professionals working in the areas of data mining, business intelligence, and analytics; data scientists; IT specialists; managers; researchers; academicians; practitioners; and graduate students. |
| automation in business intelligence: 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. |
| automation in business intelligence: Theory and Practice of Business Intelligence in Healthcare Khuntia, Jiban, Ning, Xue, Tanniru, Mohan, 2019-12-27 Business intelligence supports managers in enterprises to make informed business decisions in various levels and domains such as in healthcare. These technologies can handle large structured and unstructured data (big data) in the healthcare industry. Because of the complex nature of healthcare data and the significant impact of healthcare data analysis, it is important to understand both the theories and practices of business intelligence in healthcare. Theory and Practice of Business Intelligence in Healthcare is a collection of innovative research that introduces data mining, modeling, and analytic techniques to health and healthcare data; articulates the value of big volumes of data to health and healthcare; evaluates business intelligence tools; and explores business intelligence use and applications in healthcare. While highlighting topics including digital health, operations intelligence, and patient empowerment, this book is ideally designed for healthcare professionals, IT consultants, hospital directors, data management staff, data analysts, hospital administrators, executives, managers, academicians, students, and researchers seeking current research on the digitization of health records and health systems integration. |
| automation in business intelligence: Practical Business Intelligence Ahmed Sherif, 2016-12-21 Learn to get the most out of your business data to optimize your business About This Book This book will enable and empower you to break free of the shackles of spreadsheets Learn to make informed decisions using the data at hand with this highly practical, comprehensive guide This book includes real-world use cases that teach you how analytics can be put to work to optimize your business Using a fictional transactional dataset in raw form, you'll work your way up to ultimately creating a fully-functional warehouse and a fleshed-out BI platform Who This Book Is For This book is for anyone who has wrangled with data to try to perform automated data analysis through visualizations for themselves or their customers. This highly-customized guide is for developers who know a bit about analytics but don't know how to make use of it in the field of business intelligence. What You Will Learn Create a BI environment that enables self-service reporting Understand SQL and the aggregation of data Develop a data model suitable for analytical reporting Connect a data warehouse to the analytic reporting tools Understand the specific benefits behind visualizations with D3.js, R, Tableau, QlikView, and Python Get to know the best practices to develop various reports and applications when using BI tools Explore the field of data analysis with all the data we will use for reporting In Detail Business Intelligence (BI) is at the crux of revolutionizing enterprise. Everyone wants to minimize losses and maximize profits. Thanks to Big Data and improved methodologies to analyze data, Data Analysts and Data Scientists are increasingly using data to make informed decisions. Just knowing how to analyze data is not enough, you need to start thinking how to use data as a business asset and then perform the right analysis to build an insightful BI solution. Efficient BI strives to achieve the automation of data for ease of reporting and analysis. Through this book, you will develop the ability to think along the right lines and use more than one tool to perform analysis depending on the needs of your business. We start off by preparing you for data analytics. We then move on to teach you a range of techniques to fetch important information from various databases, which can be used to optimize your business. The book aims to provide a full end-to-end solution for an environment setup that can help you make informed business decisions and deliver efficient and automated BI solutions to any company. It is a complete guide for implementing Business intelligence with the help of the most powerful tools like D3.js, R, Tableau, Qlikview and Python that are available on the market. Style and approach Packed with real-world examples, this pragmatic guide helps you polish your data and make informed decisions for your business. We cover both business and data analysis perspectives, blending theory and practical hands-on work so that you perceive data as a business asset. |
| automation in business intelligence: Research Anthology on Artificial Intelligence Applications in Security Management Association, Information Resources, 2020-11-27 As industries are rapidly being digitalized and information is being more heavily stored and transmitted online, the security of information has become a top priority in securing the use of online networks as a safe and effective platform. With the vast and diverse potential of artificial intelligence (AI) applications, it has become easier than ever to identify cyber vulnerabilities, potential threats, and the identification of solutions to these unique problems. The latest tools and technologies for AI applications have untapped potential that conventional systems and human security systems cannot meet, leading AI to be a frontrunner in the fight against malware, cyber-attacks, and various security issues. However, even with the tremendous progress AI has made within the sphere of security, it’s important to understand the impacts, implications, and critical issues and challenges of AI applications along with the many benefits and emerging trends in this essential field of security-based research. Research Anthology on Artificial Intelligence Applications in Security seeks to address the fundamental advancements and technologies being used in AI applications for the security of digital data and information. The included chapters cover a wide range of topics related to AI in security stemming from the development and design of these applications, the latest tools and technologies, as well as the utilization of AI and what challenges and impacts have been discovered along the way. This resource work is a critical exploration of the latest research on security and an overview of how AI has impacted the field and will continue to advance as an essential tool for security, safety, and privacy online. This book is ideally intended for cyber security analysts, computer engineers, IT specialists, practitioners, stakeholders, researchers, academicians, and students interested in AI applications in the realm of security research. |
| automation in business intelligence: Augmented Exploitation Phoebe V. Moore, Jamie Woodcock, 2021 Artificial intelligence should be changing society, not reinforcing capitalist notions of work. |
| automation in business intelligence: Softwar Matthew Symonds, 2013-04-30 In a business where great risks, huge fortunes, and even bigger egos are common, Larry Ellison stands out as one of the most outspoken, driven, and daring leaders of the software industry. The company he cofounded and runs, Oracle, is the number one business software company: perhaps even more than Microsoft's, Oracle's products are essential to today's networked world. But Oracle is as controversial as it is influential, as feared as it is revered, thanks in large part to Larry Ellison. Though Oracle is one of the world's most valuable and profitable companies, Ellison is not afraid to suddenly change course and reinvent Oracle in the pursuit of new and ever more ambitious goals. Softwar examines the results of these shifts in strategy and the forces that drive Ellison relentlessly on. In Softwar, journalist Matthew Symonds gives readers an exclusive and intimate insight into both Oracle and the man who made it and runs it. As well as relating the story of Oracle's often bumpy path to industry dominance, Symonds deals with the private side of Ellison's life. From Ellison's troubled upbringing by adoptive parents and his lifelong search for emotional security to the challenges and opportunities that have come with unimaginable wealth, Softwar gets inside the skin of a fascinating and complicated human being. With unlimited insider access granted by Ellison himself, Symonds captures the intensity and, some would say, the recklessness that have made Ellison a legend. The result of more than a hundred hours of interviews and many months spent with Ellison, Softwar is the most complete portrait undertaken of the man and his empire -- a unique and gripping account of both the way the computing industry really works and an extraordinary life. Despite his closeness to Ellison, Matthew Symonds is a candid and at times highly critical observer. And in perhaps the book's most unusual feature, Ellison responds to Symonds's portrayal in the form of a running footnoted commentary. The result is one of the most fascinating business stories of all time. |
| automation in business intelligence: Data-Driven Business Intelligence Systems for Socio-Technical Organizations Keikhosrokiani, Pantea, 2024-04-09 The convergence of modern technology and social dynamics have shaped the very fabric of today’s organizations, making the role of Business Intelligence (BI) profoundly significant. Data-Driven Business Intelligence Systems for Socio-Technical Organizations delves into the heart of this transformative realm, offering an academic exploration of the tools, strategies, and methodologies that propel enterprises toward data-driven decision-making excellence. Socio-technical organizations, with their intricate interplay between human and technological components, require a unique approach to BI. This book embarks on a comprehensive journey, revealing how BI tools empower these entities to decipher the complexities of their data landscape. From user behavior to social interactions, technological systems to environmental factors, this work sheds light on the multifaceted sources of information that inform organizational strategies. Decision-makers within socio-technical organizations leverage BI insights to discern patterns, spot trends, and uncover correlations that influence operations and the intricate social dynamics within their entities. Research covering real-time monitoring and predictive analytics equips these organizations to respond swiftly to demands and anticipate future trends, harnessing the full potential of data. The book delves into their design, development, and architectural nuances, illuminating these concepts through case studies. This book is ideal for business executives, entrepreneurs, data analysts, marketers, government officials, educators, and researchers. |
| automation in business intelligence: Hyperautomation in Business and Society Darwish, Dina, 2024-07-17 The demand for efficiency and intelligent decision-making has become paramount, prompting a crucial examination of the limitations of traditional automation. Organizations find themselves at a crossroads, searching for a transformative solution that transcends conventional approaches. Enter the era of Hyperautomation an innovative paradigm that goes beyond simple automation by integrating artificial intelligence, robotic process automation, and advanced techniques such as cognitive computing and data mining. Hyperautomation in Business and Society is a comprehensive exploration of how Hyperautomation addresses the complexities of modern challenges, offering a compelling solution to propel businesses and society into a new era of efficiency and intelligent decision-making. This book sets out to achieve a dual purpose: to enlighten and to guide. Starting with a breakdown of intelligent automation, the book progresses to dissect the latest IA technologies, platforms, and the intricate ways in which it optimizes workflows. Spanning diverse applications across sectors such as logistics, marketing, finance, and customer care, it paints a vivid picture of IA's transformative influence. Notably, it addresses the challenges faced by IA implementation, offering a nuanced exploration of real-world applications and their impact on businesses. Geared towards undergraduate and postgraduate students, researchers, and practitioners, this book is a compass for those navigating the ever-changing landscape of intelligent automation. |
| automation in business intelligence: Performance Dashboards Wayne W. Eckerson, 2005-10-27 Tips, techniques, and trends on how to use dashboard technology to optimize business performance Business performance management is a hot new management discipline that delivers tremendous value when supported by information technology. Through case studies and industry research, this book shows how leading companies are using performance dashboards to execute strategy, optimize business processes, and improve performance. Wayne W. Eckerson (Hingham, MA) is the Director of Research for The Data Warehousing Institute (TDWI), the leading association of business intelligence and data warehousing professionals worldwide that provide high-quality, in-depth education, training, and research. He is a columnist for SearchCIO.com, DM Review, Application Development Trends, the Business Intelligence Journal, and TDWI Case Studies & Solution. |
| automation in business intelligence: Intelligent Automation Pascal Bornet, Ian Barkin, Jochen Wirtz, 2020-12-17 'Instrumental for success in the fourth industrial revolution, this guidebook is unique, pragmatic, and richly illustrated.'Klaus SchwabFounder and Executive Chairman of the World Economic Forum 'One of the most important books of our times! A must-read for everyone that wants to understand how Intelligent Automation is transforming our world...'Bernard MarrInternationally bestselling author and strategic business & technology advisorauthor of The Intelligent Company 'This book is helping us understand the challenges and opportunities that automation, RPA, deep learning, and artificial intelligence represent.'Dr Kai-Fu LeeAuthor of New York Times bestseller, AI Superpowers This book is the first book on the emerging trend of intelligent automation. Also known as hyperautomation, it is a cutting-edge combination of methods and technologies involving people, organizations, machine learning, natural language processing, computer vision, robotic process automation, and more. Accessible for all audiences, this book demonstrates that adopting intelligent automation has now become a condition for business survival. It delves into the technologies leveraged by hyperautomation, new trends relating to the field, and how society and work can be reinvented with intelligent automation.Key Points Covered: What is Intelligent Automation (IA)? Why has the use of IA been expanding so rapidly? What are the benefits it unleashes for people, companies, customers, and society?How have leading organizations been able to harness the full potential of IA, at scale, and generate massive efficiency gains?What are the key trends to follow, and the right decisions that leaders need to be making to thrive in today's environment?How can IA save 10+ million lives per year, triple our global budget for education, eliminate hunger, or help protect our planet?What you will get from this book: Get the lessons learned from 100+ IA transformation successes (and failures)Benefit from the largest publicly available library of 500+ IA use cases by industry and by business functionGain access to insights garnered from 200+ IA industry experts |
| automation in business intelligence: Mastering Business Intelligence (BI) Cybellium Ltd, Unleash the Power of Data with Mastering Business Intelligence (BI) In today's data-driven world, businesses rely on Business Intelligence (BI) to transform raw data into actionable insights. BI professionals are at the forefront of this revolution, enabling organizations to make informed decisions and gain a competitive edge. Mastering Business Intelligence (BI) is your comprehensive guide to excelling in the world of BI, providing you with the knowledge, skills, and strategies to become a data-savvy expert. Your Path to BI Excellence Business Intelligence is not just about collecting data; it's about turning it into meaningful information and driving strategic outcomes. Whether you're new to BI or an experienced professional aiming to sharpen your skills, this book will empower you to master the art of Business Intelligence. What You Will Discover BI Fundamentals: Gain a deep understanding of BI concepts, methodologies, and tools, from data warehousing to data visualization. Data Analysis: Dive into data analysis techniques, data modeling, and data manipulation to extract valuable insights from diverse datasets. Data Visualization: Learn the art of storytelling through data with effective data visualization and reporting techniques. BI Tools and Technologies: Explore popular BI tools like Tableau, Power BI, and QlikView, and discover how to leverage them for maximum impact. Data Governance and Ethics: Understand the importance of data governance, data quality, and ethical considerations in BI. Career Advancement: Explore career pathways in the BI field and learn how mastering BI can open doors to exciting job opportunities. Why Mastering Business Intelligence (BI) Is Essential Comprehensive Coverage: This book provides comprehensive coverage of BI topics, ensuring you have a well-rounded understanding of BI concepts and applications. Expert Guidance: Benefit from insights and advice from experienced BI professionals and industry experts who share their knowledge and best practices. Career Advancement: BI offers a wide range of career opportunities, and this book will help you unlock your full potential in this dynamic field. Stay Ahead: In a data-driven world, mastering BI is vital for staying competitive and contributing to data-driven decision-making. Your Journey to BI Mastery Begins Here Mastering Business Intelligence (BI) is your roadmap to excelling in the world of BI and advancing your career. Whether you aspire to be a BI analyst, data scientist, or BI consultant, this guide will equip you with the skills and knowledge to achieve your goals. Mastering Business Intelligence (BI) is the ultimate resource for individuals seeking to excel in the world of Business Intelligence. Whether you are new to BI or looking to enhance your skills, this book will provide you with the knowledge and strategies to become a data-savvy expert. Don't wait; begin your journey to BI mastery today! © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com |
| automation in business intelligence: Next Generation Business Intelligence Sonar, Rajendra M., Business Intelligence (BI) has been successfully deployed by modern businesses to serve their customers and stakeholders. However, organizations increasingly look at BI to be all pervasive and realize its higher level of potential, instead of following it conventionally. The book covers the techniques, technologies and frameworks that can be used to build next generation BI. |
| automation in business intelligence: Business Intelligence and Performance Management Peter Rausch, Alaa F. Sheta, Aladdin Ayesh, 2013-02-15 During the 21st century business environments have become more complex and dynamic than ever before. Companies operate in a world of change influenced by globalisation, volatile markets, legal changes and technical progress. As a result, they have to handle growing volumes of data and therefore require fast storage, reliable data access, intelligent retrieval of information and automated decision-making mechanisms, all provided at the highest level of service quality. Successful enterprises are aware of these challenges and efficiently respond to the dynamic environment in which their business operates. Business Intelligence (BI) and Performance Management (PM) offer solutions to these challenges and provide techniques to enable effective business change. The important aspects of both topics are discussed within this state-of-the-art volume. It covers the strategic support, business applications, methodologies and technologies from the field, and explores the benefits, issues and challenges of each. Issues are analysed from many different perspectives, ranging from strategic management to data technologies, and the different subjects are complimented and illustrated by numerous examples of industrial applications. Contributions are authored by leading academics and practitioners representing various universities, research centres and companies worldwide. Their experience covers multiple disciplines and industries, including finance, construction, logistics, and public services, amongst others. Business Intelligence and Performance Management is a valuable source of reference for graduates approaching MSc or PhD programs and for professionals in industry researching in the fields of BI and PM for industrial application. |
| automation in business intelligence: Handbook of Research on Applied AI for International Business and Marketing Applications Christiansen, Bryan, Škrinjari?, Tihana, 2020-09-25 Artificial intelligence (AI) describes machines/computers that mimic cognitive functions that humans associate with other human minds, such as learning and problem solving. As businesses have evolved to include more automation of processes, it has become more vital to understand AI and its various applications. Additionally, it is important for workers in the marketing industry to understand how to coincide with and utilize these techniques to enhance and make their work more efficient. The Handbook of Research on Applied AI for International Business and Marketing Applications is a critical scholarly publication that provides comprehensive research on artificial intelligence applications within the context of international business. Highlighting a wide range of topics such as diversification, risk management, and artificial intelligence, this book is ideal for marketers, business professionals, academicians, practitioners, researchers, and students. |
| automation in business intelligence: Business Intelligence Carlo Vercellis, 2011-08-10 Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. This book: Combines detailed coverage with a practical guide to the mathematical models and analysis methodologies of business intelligence. Covers all the hot topics such as data warehousing, data mining and its applications, machine learning, classification, supply optimization models, decision support systems, and analytical methods for performance evaluation. Is made accessible to readers through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real-life case studies. Explains how to utilise mathematical models and analysis models to make effective and good quality business decisions. This book is aimed at postgraduate students following data analysis and data mining courses. Researchers looking for a systematic and broad coverage of topics in operations research and mathematical models for decision-making will find this an invaluable guide. |
| automation in business intelligence: 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, images 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 |
| automation in business intelligence: Artificial Intelligence for Business Analytics Felix Weber, 2023-03-01 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. |
| automation in business intelligence: Intelligent Automation Marie Myers, Carol Brace, Lila Carden, 2023-11-13 Since prehistoric times, humans have invented ways to simplify daily activities to improve productivity. The most recent milestone in this journey is robotic process automation (RPA), helping to build software robots that can be leveraged to automate mundane and repetitive tasks that can be labor-intensive and prone to errors. In recent years, RPA has been integrated with emerging artificial intelligence (AI) and machine learning (ML) technologies to create what is referred to as intelligent automation (IA), emulating human actions and decision-making abilities. This book addresses the critical questions about the rise, usage, and future of IA practices. This book is structured by general personas considered as its primary target audience, ranging from: Early-stage practitioners seeking to learn effective management of IA programs Established IA practitioners seeking to drive maturity and scale Business leaders seeking to understand how to drive business value using IA Practitioners or academicians seeking to collaborate This book is strongly recommended for practitioners seeking to plan, implement, and scale IA practices in their organization and for researchers and students who intend to study strategy, implementation, and management of IA practice to accelerate the digital transformation agenda. |
| automation in business intelligence: Business Intelligence and Human Resource Management Deepmala Singh, Anurag Singh, Amizan Omar, SB Goyal, 2022-08-31 Business Intelligence (BI) is a solution to modern business problems. This book discusses the relationship between BI and Human Resource Management (HRM). In addition, it discusses how BI can be used as a strategic decision-making tool for the sustainable growth of an organization or business. BI helps organizations generate interactive reports with clear and reliable data for making numerous business decisions. This book covers topics spanning the important areas of BI in the context of HRM. It gives an overview of the aspects, tools, and techniques of BI and how it can assist HRM in creating a successful future for organizations. Some of the tools and techniques discussed in the book are analysis, data preparation, BI-testing, implementation, and optimization on GR and management disciplines. It will include a chapter on text mining as well as a section of case studies for practical use. This book will be useful for business professionals, including but not limited to, HR professionals, and budding business students. |
| automation in business intelligence: Intelligent Automation Simplified DEBANJANA DASGUPTA, 2021-11-02 A guide to understand the potential of Intelligent Automation across businesses and enterprises. KEY FEATURES ● A comprehensive discussion of key concepts, techniques, and key elements of intelligent automation. ● Expert coverage on combining various technologies, including RPA, AI, Blockchain, and IoT. ● Includes case studies and use cases for successful automation applications. ● Precise guidance on how to scale automation in enterprises. DESCRIPTION 'Intelligent Automation Simplified' guides tech professionals to take a much more simplified and sophisticated step towards developing intelligent automation. This book will explain the basic concepts of smart automation and how to put it into practice for a company. This book explores each stage of automation design and explains how these automation fragments can be brought together in the end-to-end automation of workflow. This book discusses numerous examples and scenarios that will help relate and understand how technology can be used in real life to solve business problems. This book provides a lot of information and insights and helps readers grasp the methodology used to develop an automation solution correctly. With detailed illustrations and real use-cases, you will be able to easily create smart automation solutions and practice how to modify them. Towards the end, the book describes how smart automation expands in a company and discusses the various strategies for large-scale use. The book also highlights the latest trends in intelligent automation and its progress into the future of work. WHAT YOU WILL LEARN ● Learn about the essential and primary components of intelligent automation. ● Investigate the capabilities of RPA and AI in the development of Intelligent Automation solutions. ● Recognize the factors that will help you choose the best processes for automation. ● Learn how to use the framework to create an Intelligent Automation solution. ● Create a blueprint to scale automation in the enterprise. ● Discover the most recent Intelligent Automation trends from industry experts. WHO THIS BOOK IS FOR This book is intended for current and future technical professionals who want to learn about Intelligent Automation, plan, and implement it in an enterprise or consult with clients. Readers should be familiar with the software development workflow and have a basic understanding of advanced technologies such as AI and RPA. TABLE OF CONTENTS 1. Introduction to Intelligent Automation 2. Robotic Process Automation 3. Artificial Intelligence in Automation 4. Other technologies in Automation 5. Intelligent Automation Use cases 6. Enterprise Automation Journey 7. Intelligent Automation – Trends and the future |
| automation in business intelligence: Artificial Intelligence in Industrial Decision Making, Control and Automation S.G. Tzafestas, H. B. Verbruggen, 2012-12-06 This book is concerned with Artificial Intelligence (AI) concepts and techniques as applied to industrial decision making, control and automation problems. The field of AI has been expanded enormously during the last years due to that solid theoretical and application results have accumulated. During the first stage of AI development most workers in the field were content with illustrations showing ideas at work on simple problems. Later, as the field matured, emphasis was turned to demonstrations that showed the capability of AI techniques to handle problems of practical value. Now, we arrived at the stage where researchers and practitioners are actually building AI systems that face real-world and industrial problems. This volume provides a set of twenty four well-selected contributions that deal with the application of AI to such real-life and industrial problems. These contributions are grouped and presented in five parts as follows: Part 1: General Issues Part 2: Intelligent Systems Part 3: Neural Networks in Modelling, Control and Scheduling Part 4: System Diagnostics Part 5: Industrial Robotic, Manufacturing and Organizational Systems Part 1 involves four chapters providing background material and dealing with general issues such as the conceptual integration of qualitative and quantitative models, the treatment of timing problems at system integration, and the investigation of correct reasoning in interactive man-robot systems. |
| automation in business intelligence: Implementing Business Intelligence Solutions Leveraging Data Analytics for Enhanced Decision-Making SURAJ DHARMAPURAM ANTONY SATYA VIVEK VARDHAN AKISETTY RAFA ABDUL DR. SINGH RAJ, 2024-11-10 In the ever-evolving landscape of the modern world, the synergy between technology and management has become a cornerstone of innovation and progress. This book, Implementing Business Intelligence Solutions: Leveraging Data Analytics for Enhanced Decision-Making, is conceived to bridge the gap between emerging technological advancements in data analytics and their strategic application in business management. Our objective is to equip readers with the tools and insights necessary to excel in this dynamic intersection of fields. This book is structured to provide a comprehensive exploration of the methodologies and strategies that define the innovation of business intelligence (BI) solutions and their integration into decision-making practices. From foundational theories to advanced applications, we delve into the critical aspects that drive successful BI initiatives in various industries. We have made a concerted effort to present complex concepts in a clear and accessible manner, making this work suitable for a diverse audience, including students, managers, and industry professionals. In authoring this book, we have drawn upon the latest research and best practices to ensure that readers not only gain a robust theoretical understanding but also acquire practical skills that can be applied in real-world scenarios. The chapters are designed to strike a balance between depth and breadth, covering topics ranging from technological development and data analytics adoption to the strategic management of BI initiatives. Additionally, we emphasize the importance of effective communication, dedicating sections to the art of presenting data-driven insights and solutions in a precise and academically rigorous manner. The inspiration for this book arises from a recognition of the crucial role that business intelligence and data analytics play in shaping the future of business decision-making. We are profoundly grateful to Chancellor Shri Shiv Kumar Gupta of Maharaja Agrasen Himalayan Garhwal University for his unwavering support and vision. His dedication to fostering academic excellence and promoting a culture of innovation has been instrumental in bringing this project to fruition. We hope this book will serve as a valuable resource and inspiration for those eager to deepen their understanding of how data analytics and BI can be harnessed together to drive business innovation. We believe that the knowledge and insights contained within these pages will empower readers to lead the way in creating data-driven solutions that will define the future of business decision-making. Thank you for joining us on this journey. Authors |
| automation in business intelligence: Business Intelligence And Analytics Prof. (Dr.) Sugandha Singh, 2023-12-27 In the fast changing world of modern business, the book Business Intelligence and Analytics serves as a complete guide, unraveling the complexities of strategically using data. As data becomes a critical asset for organizations, this book will become a must-have resource for professionals, executives, and students navigating the intricate interaction of information, technology, and decision-making. Beginning with the foundations of data collection and storage and progressing to advanced subjects such as predictive modelling, machine learning, and artificial intelligence, the book provides a full investigation of business intelligence and analytics. Readers acquire a comprehensive overview of the tools and processes defining the data-driven decision-making environment by covering the whole range. The book incorporates real-world examples and case studies to demonstrate essential topics and is rich in practical insights. The incorporation of theoretical ideas into concrete situations bridges the gap between theory and application, providing readers with a better knowledge of how to implement business intelligence techniques in a variety of organizational contexts. The book is aimed at a wide range of readers, including corporate leaders, data analysts, and students. Whether you are a seasoned business leader looking for a strategic data advantage, an analyst looking for relevant insights, or a student laying the groundwork, this book is a flexible and approachable resource for all levels of experience. |
| automation in business intelligence: Business Intelligence Rimvydas Skyrius, 2021-03-08 This book examines the managerial dimensions of business intelligence (BI) systems. It develops a set of guidelines for value creation by implementing business intelligence systems and technologies. In particular the book looks at BI as a process – driven by a mix of human and technological capabilities – to serve complex information needs in building insights and providing aid in decision making. After an introduction to the key concepts of BI and neighboring areas of information processing, the book looks at the complexity and multidimensionality of BI. It tackles both data integration and information integration issues. Bodies of knowledge and other widely accepted collections of experience are presented and turned into lessons learned. Following a straightforward introduction to the processes and technologies of BI the book embarks on BI maturity and agility, the components, drivers and inhibitors of BI culture and soft BI factors like attention, sense and trust. Eventually the book attempts to provide a holistic view on business intelligence, possible structures and tradeoffs and embarks to provide an outlook on possible developments in BI and analytics. |
| automation in business intelligence: Virtualized Business Intelligence with InfoSphere Warehouse Adriana Carvajal, Thomas Chong, IBM Redbooks, 2012-10-05 With the benefit of advanced analytics such as online analytical processing (OLAP), data mining, and text analytics, the IBM® InfoSphere® Warehouse Enterprise Edition brings sophisticated business intelligence (BI) to warehouse users. InfoSphere Warehouse allows you to run extreme concurrent query volumes that can help answer questions for all types of business users, while consistently meeting service level requirements. Combined with a virtualization platform and a solid BI solution, such as IBM Cognos®, you can deliver BI cloud services with improved flexibility and speed to your clients, thereby presenting a new avenue for which your services can be offered. This IBM Redbooks® publication discusses the deployment of a BI cloud solution. It includes details such as understanding the architecture of a cloud, planning implementation, integrating various software components, and understanding the preferred practices of running a cloud deployment. Essentially, this book can be used as a guide by anyone who is interested in deploying a virtualized environment for a BI cloud solution. |
The rise in automation and what it means for the future
Apr 7, 2021 · As with SpaceX, automation will be the way telecom providers seek to deliver reliable services and it is the foundation of leading technology companies' lofty ambitions. With …
Recession and Automation Changes Our Future of Work, But …
Oct 20, 2020 · By 2025, automation and a new division of labour between humans and machines will disrupt 85 million jobs globally in medium and large businesses across 15 industries and …
Automation or augmentation? This is how AI will be integrated …
Sep 18, 2023 · Only 16.1% of an HR manager’s job shows potential for automation and 22.2% for augmentation, according to the Jobs of Tomorrow report. The automatable tasks include …
The Future of Jobs Report 2025 | World Economic Forum
Jan 7, 2025 · Advancements in technologies, particularly AI and information processing (86%); robotics and automation (58%); and energy generation, storage and distribution (41%), are …
3 reasons why industrial automation matters - The World …
Jan 17, 2022 · Industrial automation, almost by definition, means companies require fewer employees and different skillsets. Many old-style manual jobs are vanishing, and being …
What impact will automation have on our future society? Here are …
Feb 28, 2018 · Furthermore, automation comes at a cost, which could make it financially unattractive to automate certain jobs, even if it might be imaginable from a scientific point of …
Future of Jobs Report 2025: These are the fastest growing and …
Jan 9, 2025 · Robots and automation, meanwhile, are forecast to displace 5 million more jobs than they create. Businesses expect these trends to cause a sharp fall in roles, including …
How automation gives healthcare workers time for patients
Jan 16, 2025 · Intelligent automation – a combination of AI, digital tools and robotics – is already reducing the administrative burden on healthcare workers and expanding access to more …
A short history of jobs and automation - The World Economic Forum
Sep 3, 2020 · Automation and the future According to many estimates, there will be more jobs created over the next few years than lost by automation . The challenge facing world leaders …
AI is transforming finance, CFOs say. Here's how - The World …
Mar 25, 2025 · “In large-scale organizations, AI and automation are no longer just efficiency tools— they are fundamental to financial resilience, operational agility and customer-centric …
The rise in automation and what it means for the future
Apr 7, 2021 · As with SpaceX, automation will be the way telecom providers seek to deliver reliable services and it is the foundation of leading technology companies' lofty ambitions. With the …
Recession and Automation Changes Our Future of Work, But There …
Oct 20, 2020 · By 2025, automation and a new division of labour between humans and machines will disrupt 85 million jobs globally in medium and large businesses across 15 industries and 26 …
Automation or augmentation? This is how AI will be integrated into …
Sep 18, 2023 · Only 16.1% of an HR manager’s job shows potential for automation and 22.2% for augmentation, according to the Jobs of Tomorrow report. The automatable tasks include …
The Future of Jobs Report 2025 | World Economic Forum
Jan 7, 2025 · Advancements in technologies, particularly AI and information processing (86%); robotics and automation (58%); and energy generation, storage and distribution (41%), are also …
3 reasons why industrial automation matters - The World Economic …
Jan 17, 2022 · Industrial automation, almost by definition, means companies require fewer employees and different skillsets. Many old-style manual jobs are vanishing, and being replaced …
What impact will automation have on our future society? Here are …
Feb 28, 2018 · Furthermore, automation comes at a cost, which could make it financially unattractive to automate certain jobs, even if it might be imaginable from a scientific point of …
Future of Jobs Report 2025: These are the fastest growing and …
Jan 9, 2025 · Robots and automation, meanwhile, are forecast to displace 5 million more jobs than they create. Businesses expect these trends to cause a sharp fall in roles, including various …
How automation gives healthcare workers time for patients
Jan 16, 2025 · Intelligent automation – a combination of AI, digital tools and robotics – is already reducing the administrative burden on healthcare workers and expanding access to more …
A short history of jobs and automation - The World Economic Forum
Sep 3, 2020 · Automation and the future According to many estimates, there will be more jobs created over the next few years than lost by automation . The challenge facing world leaders and …
AI is transforming finance, CFOs say. Here's how - The World …
Mar 25, 2025 · “In large-scale organizations, AI and automation are no longer just efficiency tools— they are fundamental to financial resilience, operational agility and customer-centric innovation. …
