Big Data Imperatives

Big Data Imperatives, focuses on resolving the key questions on everyone's mind: Which data matters? Do you have enough data volume to justify the usage? How you want to process this amount of data? How long do you really need to keep it active for your analysis, marketing, and BI applications? Big data is emerging from the realm of one-off projects to mainstream business adoption; however, the real value of big data is not in the overwhelming size of it, but more in its effective use. Big Data Imperatives describes the complementary nature of traditional data warehouses and big-data analytics platforms and how they feed each other. This book aims to bring the big data and analytics realms together with a greater focus on architectures that leverage the scale and power of big data and the ability to integrate and apply analytics principles to data which earlier was not accessible. This book can also be used as a handbook for practitioners; helping them on methodology,technical architecture, analytics techniques and best practices. At the same time, this book intends to hold the interest of those new to big data and analytics by giving them a deep insight into the realm of big data.

Webber, Henry Y. Zheng, Ying Zhou

Written by a leading expert in the field, this guide focuses on the convergence of two major trends in information management--big data and information governance--by taking a strategic approach oriented around business cases and industry imperatives. With the advent of new technologies, enterprises are expanding and handling very large volumes of data; this book, nontechnical in nature and geared toward business audiences, encourages the practice of establishing appropriate governance over big data initiatives and addresses how to manage and govern big data, highlighting the relevant processes, procedures, and policies. It teaches readers to understand how big data fits within an overall information governance program; quantify the business value of big data; apply information governance concepts such as stewardship, metadata, and organization structures to big data; appreciate the wide-ranging business benefits for various industries and job functions; sell the value of big data governance to businesses; and establish step-by-step processes to implement big data governance.

This book presents and discusses the main strategic and organizational challenges posed by Big Data and analytics in a manner relevant to both practitioners and scholars. The first part of the book analyzes strategic issues relating to the growing relevance of Big Data and analytics for competitive advantage, which is also attributable to empowerment of activities such as consumer profiling, market segmentation, and development of new products or services. Detailed consideration is also given to the strategic impact of Big Data and analytics on innovation in domains such as government and education and to Big Data-driven business models. The second part of the book addresses the impact of Big Data and analytics on management and organizations, focusing on challenges for governance, evaluation, and change management, while the concluding part reviews real examples of Big Data and analytics innovation at the global level. The text is supported by informative illustrations and case studies, so that practitioners can use the book as a toolbox to improve understanding and exploit business opportunities related to Big Data and analytics.

Two world-renowned strategists detail the seven leadership imperatives for transforming companies in the new digital era. Digital transformation is critical. But winning in today's world requires more than digitization. It requires understanding that the nature of competitive advantage has shifted—and that being digital is not enough. In Beyond Digital, Paul Leinwand and Matt Mani from Strategy&, PwC's global strategy consulting business, take readers inside twelve companies and how they have navigated through this monumental shift: from Philips's reinvention from a broad conglomerate to a focused health technology player, to Cleveland Clinic's engagement with its broader ecosystem to improve and expand its leading patient care to more locations around the world, to Microsoft's overhaul of its global commercial business to drive customer outcomes. Other case studies include Adobe, Citigroup, Eli Lilly, Hitachi, Honeywell, Inditex, Komatsu, STC Pay, and Titan. Building on a major new body of research, the authors identify the seven imperatives that leaders must follow as the digital age continues to evolve: Reimagine your company's place in the world Embrace and create value via ecosystems Build a system of privileged insights with your customers Make your organization outcome-oriented Invert the focus of your leadership team Reinvent the social contract with your people Disrupt your own leadership approach Together, these seven imperatives comprise a playbook for how leaders can define a bolder purpose and transform their organizations.

Drawing on a range of methods from across science and technology studies, digital humanities and digital arts, this book presents a comprehensive view of the big data phenomenon. Big data architectures are increasingly transforming political questions into technical management by determining classificatory systems in the social, educational, and healthcare realms. Data, and their multiple arborisations, have become new epistemic landscapes. They have also become new existential terrains. The fundamental question is: can big data be seen as a new medium in the way photography or film were when they first appeared? No new medium is ever truly new. It’s always remediation of older media. What is new is the medium’s re-articulation of the difference between here and there, before and after, yours and mine, knowable and unknowable, possible and impossible. This transdisciplinary volume, incorporating cultural and media theory, art, philosophy, history, and political philosophy is a key resource for readers interested in digital humanities, cultural, and media studies.

Explore why — now more than ever — the world is in a race to become data-driven, and how you can learn from examples of data-driven leadership in an Age of Disruption, Big Data, and AI In Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI, Fortune 1000 strategic advisor, noted author, and distinguished thought leader Randy Bean tells the story of the rise of Big Data and its business impact – its disruptive power, the cultural challenges to becoming data-driven, the importance of data ethics, and the future of data-driven AI. The book looks at the impact of Big Data during a period of explosive information growth, technology advancement, emergence of the Internet and social media, and challenges to accepted notions of data, science, and facts, and asks what it means to become "data-driven." Fail Fast, Learn Faster includes discussions of: The emergence of Big Data and why organizations must become data-driven to survive Why becoming data-driven forces companies to "think different" about their business The state of data in the corporate world today, and the principal challenges Why companies must develop a true "data culture" if they expect to change Examples of companies that are demonstrating data-driven leadership and what we can learn from them Why companies must learn to "fail fast and learn faster" to compete in the years ahead How the Chief Data Officer has been established as a new corporate profession Written for CEOs and Corporate Board Directors, data professional and practitioners at all organizational levels, university executive programs and students entering the data profession, and general readers seeking to understand the Information Age and why data, science, and facts matter in the world in which we live, Fail Fast, Learn Faster p;is essential reading that delivers an urgent message for the business leaders of today and of the future.

This book constitutes the proceedings of the International Conference on Big Data Intelligence and Computing, DataCom 2022, which took place in Denarau Island, Fiji, in December 2022. The 30 full papers included in this volume were carefully reviewed and selected from 88 submissions. The papers detail big data analytics solutions, distributed computation paradigms, on-demand services, autonomic systems, and pervasive applications.