William Giovinazzo gives experienced database professionals practical guidance for every aspect of planning and deploying Web-based data warehouses -- and leveraging them for competitive advantage. Unlike previous books, The Web-Enabled Data Warehouse covers all the enabling technologies and analysis approaches you need to know about -- from XML to CRM, Java to customer profiling. Giovinazzo begins by introducing the compelling advantages of integrating business intelligence and data warehouses with Web technology. He reviews the business and technical contexts in which the Web-enabled data warehouse will operate; shows how to build and optimize data warehouse infrastructure, and presents in-depth coverage of key enabling technologies -- including Java, XML and XSL, LDAP directories, and WAP wireless development environments. In the book's final section, Giovinazzo introduces and explains powerful new analysis techniques that can dramatically improve your understanding of customers -- and shows how to integrate data warehouses with CRM and other enterprise systems so you can act on your knowledge far more quickly and efficiently. For every experienced database professional seeking to understand or deploy Web-based data warehouses.

Publisher Fact Sheet How to leverage corporate information for reduced costs & increased profits.

Annotation Business Intelligence in the Digital Economy: Opportunities, Limitations and Risks describes business intelligence (BI), how it is being conducted and managed and its major opportunities, limitations, issues and risks. This book takes an in-depth look at the scope of global technological change and BI. During this transition to BI, information does not merely add efficiency to the transaction; it adds value. This book brings together high quality expository discussions from experts in this field to identify, define, and explore BI methodologies, systems, and approaches in order to understand the opportunities, limitations and risks.

You go online to buy a digital camera. Soon, you realize you've bought a more expensive camera than intended, along with extra batteries, charger, and graphics software-all at the prompting of the retailer. Happy with your purchases? The retailer certainly is, and if you are too, you both can be said to be the beneficiaries of "customer intimacy" achieved through the transformation of data collected during this visit or stored from previous visits into real business intelligence that can be exercised in real time. Data Warehousing and Business Intelligence for e-Commerce is a practical exploration of the technological innovations through which traditional data warehousing is brought to bear on this and other less modest e-commerce applications, such as those at work in B2B, G2C, B2G, and B2E models. The authors examine the core technologies and commercial products in use today, providing a nuts-and-bolts understanding of how you can deploy customer and product data in ways that meet the unique requirements of the online marketplace-particularly if you are part of a brick-and-mortar company with specific online aspirations. In so doing, they build a powerful case for investment in and aggressive development of these approaches, which are likely to separate winners from losers as e-commerce grows and matures. * Includes the latest from successful data warehousing consultants whose work has encouraged the field's new focus on e-commerce. * Presents information that is written for both consultants and practitioners in companies of all sizes. * Emphasizes the special needs and opportunities of traditional brick-and-mortar businesses that are going online or participating in B2B supply chains or e-marketplaces. * Explains how long-standing assumptions about data warehousing have to be rethought in light of emerging business models that depend on customer intimacy. * Provides advice on maintaining data quality and integrity in environments marked by extensive customer self-input. * Advocates careful planning that will help both old economy and new economy companies develop long-lived and successful e-commerce strategies. * Focuses on data warehousing for emerging e-commerce areas such as e-government and B2E environments.

Business intelligence--the acquisition, management, and utilization of information--is crucial in the global marketplace of the 21st century. This savvy handbook explains how even the smallest firm can use inexpensive Web resources to create an Internet Business Intelligence System (IBIS) that rivals the multimillion-dollar systems of Fortune 500 companies. IBIS tracks competitors, explore markets, and evaluates opportunities and risks. It can also be used to launch a business, find customers, test new products, and increase sales.

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.

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.