Vivek Kale – författare

Enterprise Process Management Systems: Engineering Process-Centric Enterprise Systems using BPMN 2.0 proposes a process-centric paradigm to replace the traditional data-centric paradigm for Enterprise Systems (ES)--ES should be reengineered from the present data-centric enterprise architecture to process-centric process architecture to be called as Enterprise Process Management Systems (EPMS).

The real significance of business processes can be understood in the context of current heightened priority on digital transformation or digitalization of enterprises. Conceiving the roadmap to realize a digitalized enterprise via the business model innovation becomes amenable only from the process-centric view of the enterprise.

This pragmatic book:

Enterprise Process Management Systems: Engineering Process-Centric Enterprise Systems using BPMN 2.0 describes how BPMN 2.0 can not only capture business requirements but it can also provide the backbone of the actual solution implementation. Thus, the same diagram prepared by the business analyst to describe the business’s desired To-Be process can also be used to automate the execution of that process on a modern process engine.

Enterprise Process Management Systems: Engineering Process-Centric Enterprise Systems using BPMN 2.0 proposes a process-centric paradigm to replace the traditional data-centric paradigm for Enterprise Systems (ES)--ES should be reengineered from the present data-centric enterprise architecture to process-centric process architecture to be called as Enterprise Process Management Systems (EPMS).

The real significance of business processes can be understood in the context of current heightened priority on digital transformation or digitalization of enterprises. Conceiving the roadmap to realize a digitalized enterprise via the business model innovation becomes amenable only from the process-centric view of the enterprise.

This pragmatic book:

Enterprise Process Management Systems: Engineering Process-Centric Enterprise Systems using BPMN 2.0 describes how BPMN 2.0 can not only capture business requirements but it can also provide the backbone of the actual solution implementation. Thus, the same diagram prepared by the business analyst to describe the business’s desired To-Be process can also be used to automate the execution of that process on a modern process engine.

"A highly readable and yet comprehensive book on network businesses that have become governable with the advent of cloud and big data computing. Vivek Kale is a master of simplifying the complex world of network theory and its relevance to business."—Jagdish N. Sheth, Charles H. Kellstadt Professor of Marketing, Emory University

Agile Network Businesses: Collaboration, Coordination, and Competitive Advantage reflects the shift from traditional networks to virtual and agile networks that enable businesses to operate dynamically, thereby representing markets more closely. This book enables IT managers and business decision-makers to understand clearly what network businesses and enterprises are, what they can do for them, and how to realize them.

Customers in geographically dispersed markets are demanding higher quality products in a greater variety, at lower cost, and in a shorter time. Thus, enterprises have moved from a few centralized and vertically integrated facilities to geographically dispersed networks of capabilities, competencies and resources, which are the core of network businesses. Enterprises are now constructing more fluid network businesses in which each member facility focuses on differentiation and relies increasingly on its partners, suppliers, and customers to provide the rest. Network businesses have emerged as an organizational paradigm for collaboration and coordination across loosely connected individual organizations.

This pragmatic book:

This book reinterprets the traditional supply chain in terms of the flow of decisions, information, and materials, which leads to reconfiguring the traditional supply chain network into mutually separate decision networks (e.g., fourth-party logistics or 4PL), information networks (e.g., wireless sensor networks), and logistics networks (e.g., third-party logistics or 3PL).

This book unravels the mystery of Big Data computing and its power to transform business operations. The approach it uses will be helpful to any professional who must present a case for realizing Big Data computing solutions or to those who could be involved in a Big Data computing project. It provides a framework that enables business and technical managers to make optimal decisions necessary for the successful migration to Big Data computing environments and applications within their organizations.

"In this book, Vivek Kale makes an important contribution to the theory and practice of enterprise architecture … this book captures the breadth and depth of information that a modern enterprise architecture must address to effectively support an agile enterprise. This book should have a place in every practicing architect''s library."

—John D. McDowall, Author of Complex Enterprise Architecture

Digital Transformation of Enterprise Architecture is the first book to propose Enterprise Architecture (EA) as the most important element (after Business Models) for digital transformation of enterprises. This book makes digital transformation more tangible by showing the rationale and typical technologies associated with it, and these technologies in turn reveal the essence of digital transformation. This book would be useful for analysts, designers and developers of future-ready agile application systems.

This book proposes that it is the perennial quest for interoperability & portability, scalability, availability, etc., that has directed and driven the evolution of the IT/IS industry in the past 50 years. It is this very quest that has led to the emergence of technologies like service-oriented, cloud, and big data computing. In addition to the conventional attributes of EA like interoperability, scalability and availability, this book identifies additional attributes of mobility, ubiquity, security, analyticity, and usability.

This pragmatic book:

Digital Transformation of Enterprise Architecture proposes that to withstand the disruptive digital storms of the future, enterprises must bring about digital transformation, i.e. a transformation that affects an exponential change (amplification or attenuation) in any aspect of the constituent attributes of EA. It proposes that each of these technologies (service-oriented, cloud, big data, context-aware, IoT, blockchain, soft, and interactive computing) bring about digital transformation of the corresponding EA attribute viz. interoperability, scalability, availability, mobility, ubiquity, security, analyticity, and usability.

"In this book, Vivek Kale makes an important contribution to the theory and practice of enterprise architecture … this book captures the breadth and depth of information that a modern enterprise architecture must address to effectively support an agile enterprise. This book should have a place in every practicing architect''s library."

—John D. McDowall, Author of Complex Enterprise Architecture

Digital Transformation of Enterprise Architecture is the first book to propose Enterprise Architecture (EA) as the most important element (after Business Models) for digital transformation of enterprises. This book makes digital transformation more tangible by showing the rationale and typical technologies associated with it, and these technologies in turn reveal the essence of digital transformation. This book would be useful for analysts, designers and developers of future-ready agile application systems.

This book proposes that it is the perennial quest for interoperability & portability, scalability, availability, etc., that has directed and driven the evolution of the IT/IS industry in the past 50 years. It is this very quest that has led to the emergence of technologies like service-oriented, cloud, and big data computing. In addition to the conventional attributes of EA like interoperability, scalability and availability, this book identifies additional attributes of mobility, ubiquity, security, analyticity, and usability.

This pragmatic book:

Digital Transformation of Enterprise Architecture proposes that to withstand the disruptive digital storms of the future, enterprises must bring about digital transformation, i.e. a transformation that affects an exponential change (amplification or attenuation) in any aspect of the constituent attributes of EA. It proposes that each of these technologies (service-oriented, cloud, big data, context-aware, IoT, blockchain, soft, and interactive computing) bring about digital transformation of the corresponding EA attribute viz. interoperability, scalability, availability, mobility, ubiquity, security, analyticity, and usability.

Parallel Computing Architectures and APIs: IoT Big Data Stream Processing commences from the point high-performance uniprocessors were becoming increasingly complex, expensive, and power-hungry. A basic trade-off exists between the use of one or a small number of such complex processors, at one extreme, and a moderate to very large number of simpler processors, at the other. When combined with a high-bandwidth, interprocessor communication facility leads to significant simplification of the design process. However, two major roadblocks prevent the widespread adoption of such moderately to massively parallel architectures: the interprocessor communication bottleneck, and the difficulty and high cost of algorithm/software development.

One of the most important reasons for studying parallel computing architectures is to learn how to extract the best performance from parallel systems. Specifically, you must understand its architectures so that you will be able to exploit those architectures during programming via the standardized APIs.

This book would be useful for analysts, designers and developers of high-throughput computing systems essential for big data stream processing emanating from IoT-driven cyber-physical systems (CPS).

This pragmatic book:

Parallel Computing Architectures and APIs: IoT Big Data Stream Processing discusses stream processing that enables the gathering, processing and analysis of high-volume, heterogeneous, continuous Internet of Things (IoT) big data streams, to extract insights and actionable results in real time. Application domains requiring data stream management include military, homeland security, sensor networks, financial applications, network management, web site performance tracking, real-time credit card fraud detection, etc.

Parallel Computing Architectures and APIs: IoT Big Data Stream Processing commences from the point high-performance uniprocessors were becoming increasingly complex, expensive, and power-hungry. A basic trade-off exists between the use of one or a small number of such complex processors, at one extreme, and a moderate to very large number of simpler processors, at the other. When combined with a high-bandwidth, interprocessor communication facility leads to significant simplification of the design process. However, two major roadblocks prevent the widespread adoption of such moderately to massively parallel architectures: the interprocessor communication bottleneck, and the difficulty and high cost of algorithm/software development.

One of the most important reasons for studying parallel computing architectures is to learn how to extract the best performance from parallel systems. Specifically, you must understand its architectures so that you will be able to exploit those architectures during programming via the standardized APIs.

This book would be useful for analysts, designers and developers of high-throughput computing systems essential for big data stream processing emanating from IoT-driven cyber-physical systems (CPS).

This pragmatic book:

Parallel Computing Architectures and APIs: IoT Big Data Stream Processing discusses stream processing that enables the gathering, processing and analysis of high-volume, heterogeneous, continuous Internet of Things (IoT) big data streams, to extract insights and actionable results in real time. Application domains requiring data stream management include military, homeland security, sensor networks, financial applications, network management, web site performance tracking, real-time credit card fraud detection, etc.

"Vivek Kale has written a great book on performance management that focuses on decision-making; on continuous, incremental improvement; and on identifying common patterns in becoming a more intelligent organization." —James Taylor, CEO of Decision Management Solutions and author of Real-World Decision Modeling with DMN

"Introducing the concepts of decision patterns and performance intelligence, Vivek Kale has written another important book on the issues faced by contemporary organizations."—Gary Cokins, author of Predictive Business Analytics and Performance Management: Integrating Strategy Execution, Methodologies, Risk, and Analytics

Enterprise Performance Intelligence and Decision Patterns unravels the mystery of enterprise performance intelligence (EPI) and explains how it can transform the operating context of business enterprises. It provides a clear understanding of what EPI means, what it can do, and application areas where it is practical to use.

The need to be responsive to evolving customer needs and desires creates organizational structures where business intelligence (BI) and decision making is pushed out to operating units that are closest to the scene of the action. Closed-loop decision making resulting from a combination of on-going performance management with on-going BI can lead to an effective responsive enterprise; hence, the need for performance intelligence (PI).

This pragmatic book:

Introduces the technologies such as data warehousing, data mining, analytics, and business intelligence systems that are a first step toward enabling data-driven enterprises.

Enterprise Performance Intelligence and Decision Patterns shows how a company can design and implement instruments ranging from decision patterns to PI systems that can enable continuous correction of business unit behavior so companies can enhance levels of productivity and profitability.

"Vivek Kale''s Creating Smart Enterprises goes smack-dab at the heart of harnessing technology for competing in today''s chaotic digital era. Actually, for him, it''s SMACT-dab: SMACT (Social media, Mobile, Analytics and big data, Cloud computing, and internet of Things) technologies. This book is required reading for those that want to stay relevant and win, and optional for those that don''t."

—Peter Fingar, Author of Cognitive Computing and business technology consultant

Creating Smart Enterprises unravels the mystery of social media, mobile, analytics and big data, cloud, and Internet of Things (SMACT) computing and explains how it can transform the operating context of business enterprises. It provides a clear understanding of what SMACT really means, what it can do for smart enterprises, and application areas where it is practical to use them.

All IT professionals who are involved with any aspect of a SMACT computing project will profit by using this book as a roadmap to make a more meaningful contribution to the success of their computing initiatives.

This pragmatic book:

This book addresses the key differentiator of SMACT computing environments and solutions that combine the power of an elastic infrastructure with analytics. The SMACT environment is cloud-based and inherently mobile. Information management processes can analyze and discern recurring patterns in colossal pools of operational and transactional data. Analytics, big data, and IoT computing leverage and transform these data patterns to help create successful, smart enterprises.

This book unravels the mystery of Big Data computing and its power to transform business operations. The approach it uses will be helpful to any professional who must present a case for realizing Big Data computing solutions or to those who could be involved in a Big Data computing project. It provides a framework that enables business and technical managers to make optimal decisions necessary for the successful migration to Big Data computing environments and applications within their organizations.