This IBM® RedpaperTM publication introduces a new data virtualization capability that enables IBM z/OS® data to be combined with other enterprise data sources in real-time, which allows applications to access any live enterprise data anytime and use the power and efficiencies of the IBM Z® platform. Modern businesses need actionable and timely insight from current data. They cannot afford the time that is necessary to copy and transform data. They also cannot afford to secure and protect each copy of personally identifiable information and corporate intellectual property. Data virtualization enables direct connections to be established between multiple data sources and the applications that process the data. Transformations can be applied, in line, to enable real-time access to data, which opens up many new ways to gain business insight with less IT infrastructure necessary to achieve those goals. Data virtualization can become the backbone for advanced analytics and modern applications. The IBM Data Virtualization Manager for z/OS (DVM) can be used as a stand-alone product or as a utility that is used by other products. Its goal is to enable access to live mainframe transaction data and make it usable by any application. This enables customers to use the strengths of mainframe processing with new agile applications. Additionally, its modern development environment and code-generating capabilities enable any developer to update, access, and combine mainframe data easily by using modern APIs and languages. If data is the foundation for building new insights, IBM DVM is a key tool for providing easy, cost-efficient access to that foundation.

This IBM® Redpaper"!publication introduces a new data virtualization capability that enables IBM z/OS® data to be combined with other enterprise data sources in real-time, which allows applications to access any live enterprise data anytime and use the power and efficiencies of the IBM Z® platform. Modern businesses need actionable and timely insight from current data. They cannot afford the time that is necessary to copy and transform data. They also cannot afford to secure and protect each copy of personally identifiable information and corporate intellectual property. Data virtualization enables direct connections to be established between multiple data sources and the applications that process the data. Transformations can be applied, in line, to enable real-time access to data, which opens up many new ways to gain business insight with less IT infrastructure necessary to achieve those goals. Data virtualization can become the backbone for advanced analytics and modern applications. The IBM Data Virtualization Manager for z/OS (DVM) can be used as a stand-alone product or as a utility that is used by other products. Its goal is to enable access to live mainframe transaction data and make it usable by any application. This this what? enables customers to use the strengths of mainframe processing with new agile applications. Additionally, its modern development environment and code-generating capabilities enable any developer to update, access, and combine mainframe data easily by using modern APIs and languages. If data is the foundation for building new insights, IBM DVM is a key tool for providing easy, cost-efficient access to that foundation

Today, organizations are responding to market demands and regulatory requirements faster than ever by extending their applications and data to new digital applications. This drive to deliver new functions at speed has paved the way for a huge growth in cloud-native applications, hosted in both public and private cloud infrastructures. Leading organizations are now exploiting the best of both worlds by combining their traditional enterprise IT with cloud. This hybrid cloud approach places new requirements on the integration architectures needed to bring these two worlds together. One of the largest providers of application logic and data services in enterprises today is IBM Z, making it a critical service provider in a hybrid cloud architecture. The primary goal of this IBM Redpaper publication is to help IT architects choose between the different application integration architectures that can be used for hybrid integration with IBM Z, including REST APIs, messaging, and event streams.

In today's fast-paced, ever-growing digital world, you face various new and complex business problems. To help resolve these problems, enterprises are embedding artificial intelligence (AI) into their mission-critical business processes and applications to help improve operations, optimize performance, personalize the user experience, and differentiate themselves from the competition. Furthermore, the use of AI on the IBM® zSystems platform, where your mission-critical transactions, data, and applications are installed, is a key aspect of modernizing business-critical applications while maintaining strict service-level agreements (SLAs) and security requirements. This colocation of data and AI empowers your enterprise to optimally and easily deploy and infuse AI capabilities into your enterprise workloads with the most recent and relevant data available in real time, which enables a more transparent, accurate, and dependable AI experience. This IBM Redpaper publication introduces and explains AI technologies and hardware optimizations, and demonstrates how to leverage certain capabilities and components to enable AI solutions in business-critical use cases, such as fraud detection and credit risk scoring, on the platform. Real-time inferencing with AI models, a capability that is critical to certain industries and use cases, now can be implemented with optimized performance thanks to innovations like IBM zSystems Integrated Accelerator for AI embedded in the Telum chip within IBM z16TM. This publication describes and demonstrates the implementation and integration of the two end-to-end solutions (fraud detection and credit risk), from developing and training the AI models to deploying the models in an IBM z/OS® V2R5 environment on IBM z16 hardware, and integrating AI functions into an application, for example an IBM z/OS Customer Information Control System (IBM CICS®) application. We describe performance optimization recommendations and considerations when leveraging AI technology on the IBM zSystems platform, including optimizations for micro-batching in IBM Watson® Machine Learning for z/OS. The benefits that are derived from the solutions also are described in detail, including how the open-source AI framework portability of the IBM zSystems platform enables model development and training to be done anywhere, including on IBM zSystems, and enables easy integration to deploy on IBM zSystems for optimal inferencing. Thus, allowing enterprises to uncover insights at the transaction-level while taking advantage of the speed, depth, and securability of the platform. This publication is intended for technical specialists, site reliability engineers, architects, system programmers, and systems engineers. Technologies that are covered include TensorFlow Serving, WMLz, IBM Cloud Pak® for Data (CP4D), IBM z/OS Container Extensions (zCX), IBM CICS, Open Neural Network Exchange (ONNX), and IBM Deep Learning Compiler (zDLC).

Digital transformation (DT) has become a buzzword. Every industry segment across the globe is consciously jumping toward digital innovation and disruption to get ahead of their competitors. In other words, every aspect of running a business is being digitally empowered to reap all the benefits of the digital paradigm. All kinds of digitally enabled businesses across the globe are intrinsically capable of achieving bigger and better things for their constituents. Their consumers, clients, and customers will realize immense benefits with real digital transformation initiatives and implementations. The much-awaited business transformation can be easily and elegantly accomplished with a workable and winnable digital transformation strategy, plan, and execution. There are several enablers and accelerators for realizing the much-discussed digital transformation. There are a lot of digitization and digitalization technologies available to streamline and speed up the process of the required transformation. Industrial Internet of Things (IIoT) technologies in close association with decisive advancements in the artificial intelligence (AI) space can bring forth the desired transitions. The other prominent and dominant technologies toward forming digital organizations include cloud IT, edge/fog computing, real-time data analytics platforms, blockchain technology, digital twin paradigm, virtual and augmented reality (VR/AR) techniques, enterprise mobility, and 5G communication. These technological innovations are intrinsically competent and versatile enough to fulfill the varying requirements for establishing and sustaining digital enterprises. Enterprise Digital Transformation: Technology, Tools, and Use Cases features chapters on the evolving aspects of digital transformation and intelligence. It covers the unique competencies of digitally transformed enterprises, IIoT use cases, and applications. It explains promising technological solutions widely associated with digital innovation and disruption. The book focuses on setting up and sustaining smart factories that are fulfilling the Industry 4.0 vision that is realized through the IIoT and allied technologies.

How to transform and compete in the digital age is foremost on every leaders' mind and the race is on for companies of all sizes to utilize data and technology to be competitive and grow. To what extent an organization can effectively transform will ultimately determine their future success or failure. Done well, a digital transformation will reduce costs, build efficiencies, and allow companies to better manage their assets, expand market share, better serve customers, and add value to existing customers and shareholders. And while most companies know that digital transformation is essential and valuable, many of them typically struggle or fail with this implementation. The results are delivered late, go over budget, or simply cannot provide the outcomes they were originally conceived for. Not to mention the millions, or in some cases billions, of dollars spent. After decades of successfully consulting with Fortune 500 companies, the team at Platinum PMO has developed procedures, practices, methodologies, and a digital transformation implementation platform that set the stage for a successful implementation of the digital transformation process. In TheTransformation, we share: -The key steps involved in digital transformation -Critical mistakes many companies make and how to avoid them -How to build the proper connections throughout your company for successful implementation from the C-suite to the ground level -How to use technology to stimulate innovation The book was written to help you understand the "story" of a digital transformation and to provide the tools and framework for understanding the underlying processes that we have learned from decades in the industry. This book's unique principles and techniques, which are needed for a successful implementation, have been embedded in a compelling story with interesting characters. It will hold your attention while you experience the process through the eyes of a new program manager, Mike Bennett, who is on a profound professional and personal journey. From inception and budgeting to implementation, quality control, and effective communication tools, The Transformation details every important aspect for a successful digital transformation. Whether your company is just starting to consider this process or is along the way, you will find this book to be an indispensable guide for taking your company or organization successfully into the digital age.

The recent surge of interest in “digital transformation” is changing the business landscape and posing several challenges, both organizational and sectoral. This transformation involves the application of digital technology in all aspects of business, and enables organizations to create new products and services, and to find more efficient ways of doing business. Moreover, the digital transformation is happening within and across organizations of all types and in every industry, producing a disruptive innovation that can break down the barriers between people and organizations, and help create more adaptive processes. In the information age, it is imperative for organizations to develop IT-related capabilities that allow them to leverage the potential of digital technologies. Due to the pervasive effects of this transformation on processes, firms and industries, both scholars and practitioners are interested in better understanding the key mechanisms behind the emergence and evolution of the digital business transformation. This book presents a collection of research papers focusing on the relationships between technologies (e.g., digital platforms, AI, blockchain, etc.), processes (e.g., decision-making, co-creation, financial, compliance, etc.), and organizations (e.g., smart organizations, digital ecosystems, Industry 4.0, collaborative networked organizations, etc.), which have been categorized into three major areas: organizing, managing and controlling. It also provides critical insights into how the digital transformation is enhancing organizational processes and firms’ performance through an exploration and exploitation of internal resources, and through the establishment of external connections and linkages. The plurality of views offered makes this book particularly relevant for users, companies, scientists, and governments. The content of the book is based on a selection of the best papers (original double-blind peer-reviewed contributions) presented at the annual conference of the Italian chapter of the AIS, which was held in Naples, Italy in September 2019.