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The Economics of Data, Analytics, and Digital Transformation

The Economics of Data, Analytics, and Digital Transformation
Author: Bill Schmarzo
Publisher: Packt Publishing Ltd
Total Pages: 261
Release: 2020-11-30
Genre: Computers
ISBN: 1800569130
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Build a continuously learning and adapting organization that can extract increasing levels of business, customer and operational value from the amalgamation of data and advanced analytics such as AI and Machine Learning Key Features Master the Big Data Business Model Maturity Index methodology to transition to a value-driven organizational mindset Acquire implementable knowledge on digital transformation through 8 practical laws Explore the economics behind digital assets (data and analytics) that appreciate in value when constructed and deployed correctly Book Description In today's digital era, every organization has data, but just possessing enormous amounts of data is not a sufficient market discriminator. The Economics of Data, Analytics, and Digital Transformation aims to provide actionable insights into the real market discriminators, including an organization's data-fueled analytics products that inspire innovation, deliver insights, help make practical decisions, generate value, and produce mission success for the enterprise. The book begins by first building your mindset to be value-driven and introducing the Big Data Business Model Maturity Index, its maturity index phases, and how to navigate the index. You will explore value engineering, where you will learn how to identify key business initiatives, stakeholders, advanced analytics, data sources, and instrumentation strategies that are essential to data science success. The book will help you accelerate and optimize your company's operations through AI and machine learning. By the end of the book, you will have the tools and techniques to drive your organization's digital transformation. Here are a few words from Dr. Kirk Borne, Data Scientist and Executive Advisor at Booz Allen Hamilton, about the book: "Data analytics should first and foremost be about action and value. Consequently, the great value of this book is that it seeks to be actionable. It offers a dynamic progression of purpose-driven ignition points that you can act upon." What you will learn Train your organization to transition from being data-driven to being value-driven Navigate and master the big data business model maturity index Learn a methodology for determining the economic value of your data and analytics Understand how AI and machine learning can create analytics assets that appreciate in value the more that they are used Become aware of digital transformation misconceptions and pitfalls Create empowered and dynamic teams that fuel your organization's digital transformation Who this book is for This book is designed to benefit everyone from students who aspire to study the economic fundamentals behind data and digital transformation to established business leaders and professionals who want to learn how to leverage data and analytics to accelerate their business careers.

Data Analytics and Digital Transformation

Data Analytics and Digital Transformation
Author: Erik Beulen
Publisher: Taylor & Francis
Total Pages: 243
Release: 2023-12-01
Genre: Business & Economics
ISBN: 1003807356
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Understanding the significance of data analytics is paramount for digital transformation but in many organizations they are separate units without fully aligned goals. As organizations are applying digital transformations to be adaptive and agile in a competitive environment, data analytics can play a critical role in their success. This book explores the crossroads between them and how to leverage their connection for improved business outcomes. The need to collaborate and share data is becoming an integral part of digital transformation. This not only creates new opportunities but also requires well-considered and continuously assessed decision-making as competitiveness is at stake. This book details approaches, concepts, and frameworks, as well as actionable insights and good practices, including combined data management and agile concepts. Critical issues are discussed such as data quality and data governance, as well as compliance, privacy, and ethics. It also offers insights into how both private and public organizations can innovate and keep up with growing data volumes and increasing technological developments in the short, mid, and long term. This book will be of direct appeal to global researchers and students across a range of business disciplines, including technology and innovation management, organizational studies, and strategic management. It is also relevant for policy makers, regulators, and executives of private and public organizations looking to implement successful transformation policies.

Business Models

Business Models
Author: Iwona Otola
Publisher: CRC Press
Total Pages: 169
Release: 2020-07-09
Genre: Business & Economics
ISBN: 100009779X
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Since the beginning of time, running a business has involved using logic by which the business operates. This logic is called the business model in management science, which increasingly is focusing on issues surrounding business models. Research trends related to business models include value creation, value chain operationalization, and social and ecological aspects, as well as innovation and digital transformation. Business Models: Innovation, Digital Transformation, and Analytics examines how innovation, digital transformation, and the composition of value affect the existence and development of business models. The book starts by addressing the conceptual development of business models and by discussing the essence of innovation in those models. Chapters in the book investigate how: Business models can analyze digital transformation scenarios Individual business model elements effect selected performance measures as well as how the elements are significant for the enterprise value composition The environment effects the profitability of the high-growth enterprise business models Employer branding business models are perceived by the generation Z workforce To implement responsible business models in the enterprise Cyber risk is captured in business models Decision algorithms are important to business analytics This book is a compendium of knowledge about the use of business models in the context of innovative activities, digital transformation, and value composition. It attempts to combine the theory and practice and offers a look at business models currently used in companies, especially high-growth enterprises, in various countries of the world and indicates the prospects for their development.

Internet of Things in Business Transformation

Internet of Things in Business Transformation
Author: Parul Gandhi
Publisher: John Wiley & Sons
Total Pages: 320
Release: 2021-02-03
Genre: Computers
ISBN: 1119711126
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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.

Data-Based Decision Making and Digital Transformation

Data-Based Decision Making and Digital Transformation
Author: Daniel J. Power
Publisher: Business Expert Press
Total Pages: 106
Release: 2018-05-31
Genre: Business & Economics
ISBN: 1631576593
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Digital disruption is accelerating. Implementing a successful digital transformation strategy requires that senior managers make trade-off decisions to reinvent a business. Equally important all decision makers must learn to ask the right questions, use data and computer support in decision making, and increase their knowledge and skills. Creating a data-centric culture and rewarding data-based decision making leads to successful digital transformation. Join the digital journey. This book is targeted at managers, especially middle-level managers who are trying to come to grips with using data-based decision making in a transforming organization. The authors explore a number of broad questions including: How can managers become data-based decision makers? How can digital transformation become part of an organi­zational strategy? What new skills do managers need to implement digital transformation? How will we know an organization has been successfully transformed?

Systems of Insight for Digital Transformation: Using IBM Operational Decision Manager Advanced and Predictive Analytics

Systems of Insight for Digital Transformation: Using IBM Operational Decision Manager Advanced and Predictive Analytics
Author: Whei-Jen Chen
Publisher: IBM Redbooks
Total Pages: 266
Release: 2015-12-03
Genre: Computers
ISBN: 073844118X
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Systems of record (SORs) are engines that generates value for your business. Systems of engagement (SOE) are always evolving and generating new customer-centric experiences and new opportunities to capitalize on the value in the systems of record. The highest value is gained when systems of record and systems of engagement are brought together to deliver insight. Systems of insight (SOI) monitor and analyze what is going on with various behaviors in the systems of engagement and information being stored or transacted in the systems of record. SOIs seek new opportunities, risks, and operational behavior that needs to be reported or have action taken to optimize business outcomes. Systems of insight are at the core of the Digital Experience, which tries to derive insights from the enormous amount of data generated by automated processes and customer interactions. Systems of Insight can also provide the ability to apply analytics and rules to real-time data as it flows within, throughout, and beyond the enterprise (applications, databases, mobile, social, Internet of Things) to gain the wanted insight. Deriving this insight is a key step toward being able to make the best decisions and take the most appropriate actions. Examples of such actions are to improve the number of satisfied clients, identify clients at risk of leaving and incentivize them to stay loyal, identify patterns of risk or fraudulent behavior and take action to minimize it as early as possible, and detect patterns of behavior in operational systems and transportation that lead to failures, delays, and maintenance and take early action to minimize risks and costs. IBM® Operational Decision Manager is a decision management platform that provides capabilities that support both event-driven insight patterns, and business-rule-driven scenarios. It also can easily be used in combination with other IBM Analytics solutions, as the detailed examples will show. IBM Operational Decision Manager Advanced, along with complementary IBM software offerings that also provide capability for systems of insight, provides a way to deliver the greatest value to your customers and your business. IBM Operational Decision Manager Advanced brings together data from different sources to recognize meaningful trends and patterns. It empowers business users to define, manage, and automate repeatable operational decisions. As a result, organizations can create and shape customer-centric business moments. This IBM Redbooks® publication explains the key concepts of systems of insight and how to implement a system of insight solution with examples. It is intended for IT architects and professionals who are responsible for implementing a systems of insights solution requiring event-based context pattern detection and deterministic decision services to enhance other analytics solution components with IBM Operational Decision Manager Advanced.

Digital Transformation for the Process Industries

Digital Transformation for the Process Industries
Author: Osvaldo A. Bascur
Publisher: CRC Press
Total Pages: 321
Release: 2020-10-27
Genre: Business & Economics
ISBN: 1000165388
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Emphasizes a culture of sustainable growth and considers how safety and environmental aspects align with profitability and production of products that satisfy customer expectations Presents how a data infrastructure enables transformation of raw data into operational insights integration with Business Intelligence tools like PowerBI, PI Vision, and predictive analytics tools such as R, Python, and cloud services Features a plant Unit Template showing how to digitize operations to transform raw data into operational insights and offers examples of developing predictive models for avoiding plant excursions and improve the running time Includes examples of companies successfully using operational information to improve yields and reduce operating costs Describes buzzwords and translates them into actual examples so engineering professionals and information systems personnel can work together as a team

Digital Transformation

Digital Transformation
Author: Thomas M. Siebel
Publisher: RosettaBooks
Total Pages: 240
Release: 2019-07-09
Genre: Business & Economics
ISBN: 0795352646
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The legendary Silicon Valley entrepreneur examines how both business and government organizations can harness the power of disruptive technologies. Tom Siebel, the billionaire technologist and founder of Siebel Systems, discusses how four technologies—elastic cloud computing, big data, artificial intelligence, and the internet of things—are fundamentally changing how business and government will operate in the 21st century. While this profound and fast-moving transformation can appear daunting to some, Siebel shows how organizations can not only survive, but thrive in the new digital landscape. In this authoritative yet accessible book, Siebel guides readers through the technologies driving digital transformation, and demonstrates how they can strategically exploit their powerful capabilities. He shows how leading enterprises such as Enel, 3M, Royal Dutch Shell, the U.S. Department of Defense, and others are applying AI and IoT with stunning results.

Data Analytics and AI

Data Analytics and AI
Author: Jay Liebowitz
Publisher: CRC Press
Total Pages: 187
Release: 2020-08-06
Genre: Computers
ISBN: 1000094677
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Analytics and artificial intelligence (AI), what are they good for? The bandwagon keeps answering, absolutely everything! Analytics and artificial intelligence have captured the attention of everyone from top executives to the person in the street. While these disciplines have a relatively long history, within the last ten or so years they have exploded into corporate business and public consciousness. Organizations have rushed to embrace data-driven decision making. Companies everywhere are turning out products boasting that "artificial intelligence is included." We are indeed living in exciting times. The question we need to ask is, do we really know how to get business value from these exciting tools? Unfortunately, both the analytics and AI communities have not done a great job in collaborating and communicating with each other to build the necessary synergies. This book bridges the gap between these two critical fields. The book begins by explaining the commonalities and differences in the fields of data science, artificial intelligence, and autonomy by giving a historical perspective for each of these fields, followed by exploration of common technologies and current trends in each field. The book also readers introduces to applications of deep learning in industry with an overview of deep learning and its key architectures, as well as a survey and discussion of the main applications of deep learning. The book also presents case studies to illustrate applications of AI and analytics. These include a case study from the healthcare industry and an investigation of a digital transformation enabled by AI and analytics transforming a product-oriented company into one delivering solutions and services. The book concludes with a proposed AI-informed data analytics life cycle to be applied to unstructured data.

A Field Guide to Digital Transformation

A Field Guide to Digital Transformation
Author: Thomas Erl
Publisher: Addison-Wesley Professional
Total Pages: 361
Release: 2021-12-22
Genre: Business & Economics
ISBN: 0137571917
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Your Complete Guide to Digital Transformation A Field Guide to Digital Transformation is the definitive book on digital transformation. Top-selling IT author Thomas Erl and long-time practitioner Roger Stoffers combine to provide comprehensive, yet easy-to-understand coverage of essential digital transformation concepts, practices, and technologies in the format of a plain-English tutorial written for any IT professionals, students, or decision-makers. With more than 160 diagrams, this guide provides a highly visual exploration of what digital transformation is, how it works, and the techniques and technologies required to successfully build modern-day digital transformation solutions. Learn from the experts and: Discover what digital transformation is, why it emerged and when to apply it Identify the significant business benefits that successful digital transformations can deliver and how to turn your organization into a “disruptive” force Prepare for and overcome the common challenges associated with digital transformation initiatives Understand the data-driven nature of digital transformation solutions and how they use and continually accumulate data intelligence Understand how digital transformation solutions can utilize AI technology for intelligent automated decision-making Gain insight into customer-centricity and how its practices are applied as part of digital transformations Explore key digital transformation automation technologies, such as Robotic Process Automation (RPA), Internet of Things (IoT), Blockchain. and Cloud Computing Explore key digital transformation data science technologies, such as Artificial Intelligence (AI), Machine Learning, and Big Data Analysis and Analytics The book concludes with a uniquely detailed and highly visual real-world business scenario that provides step-by-step insights into how a digital transformation solution works, how it utilizes data intelligence to improve customer relationship building, and how it collects new data intelligence in support of enhancing future business capabilities.