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Preventing Litigation, for the first time, explains how to build an early warning system to identify the risk of litigation before the damage is done, and proves that there is big value in less litigation. This book puts everyone where they should be: at the top of the cliff. The authors are subject matter experts, one in litigation, the other in computer science, and each has more than four decades of training and experience in their respective fields. Together, they present a way forward to a transformative revolution for the slow-moving world of law for the benefit of the fast-paced environment of the business world. Any business adopting the teachings of this pioneering, game-changing book will have a competitive advantage.
The Data and Analytics Playbook: Proven Methods for Governed Data and Analytic Quality explores the way in which data continues to dominate budgets, along with the varying efforts made across a variety of business enablement projects, including applications, web and mobile computing, big data analytics, and traditional data integration. The book teaches readers how to use proven methods and accelerators to break through data obstacles to provide faster, higher quality delivery of mission critical programs. Drawing upon years of practical experience, and using numerous examples and an easy to understand playbook, Lowell Fryman, Gregory Lampshire, and Dan Meers discuss a simple, proven approach to the execution of multiple data oriented activities. In addition, they present a clear set of methods to provide reliable governance, controls, risk, and exposure management for enterprise data and the programs that rely upon it. In addition, they discuss a cost-effective approach to providing sustainable governance and quality outcomes that enhance project delivery, while also ensuring ongoing controls. Example activities, templates, outputs, resources, and roles are explored, along with different organizational models in common use today and the ways they can be mapped to leverage playbook data governance throughout the organization. Provides a mature and proven playbook approach (methodology) to enabling data governance that supports agile implementation Features specific examples of current industry challenges in enterprise risk management, including anti-money laundering and fraud prevention Describes business benefit measures and funding approaches using exposure based cost models that augment risk models for cost avoidance analysis and accelerated delivery approaches using data integration sprints for application, integration, and information delivery success
An Executive Guide to Data Management
Counterintelligence for Corporate Environments, Volume I provides the reader with unique, comprehensive, and efficient methodologies that will change and improve corporate security and operational models to the highest degree possible. Through the extensive and sophisticated discipline of counterintelligence, readers will learn the vital importance of intelligence to the survival, efficiency, and well-being of any organization as well as a whole new approach to the protection of business intelligence and assets. Volume two discusses topics and illustrates strategies and procedures that have never before been used in the corporate field. Inspired by the concepts, strategies, and tactics that have been used by intelligence communities and specialized military forces for decades, this book aims to improve and safeguard every component of a corporate environment through the adaptation and modification of the same strategies employed by these specialized entities. Through this book, managers, security officers, consultants, and entire corporate environments will have the knowledge and skills necessary in order to change the entire dynamic of security applications in the present day and will be able to integrate advanced and highly efficient counterintelligence models in order to combat the extensive modern threat landscape.
Find the right big data solution for your business or organization Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it matters, and how to choose and implement solutions that work. Effectively managing big data is an issue of growing importance to businesses, not-for-profit organizations, government, and IT professionals Authors are experts in information management, big data, and a variety of solutions Explains big data in detail and discusses how to select and implement a solution, security concerns to consider, data storage and presentation issues, analytics, and much more Provides essential information in a no-nonsense, easy-to-understand style that is empowering Big Data For Dummies cuts through the confusion and helps you take charge of big data solutions for your organization.
It used to take years or even decades for disruptive innovations to dethrone dominant products and services. But now any business can be devastated virtually overnight by something better and cheaper. How can executives protect themselves and harness the power of Big Bang Disruption? Just a few years ago, drivers happily spent more than $200 for a GPS unit. But as smartphones exploded in popularity, free navigation apps exceeded the performance of stand-alone devices. Eighteen months after the debut of the navigation apps, leading GPS manufacturers had lost 85 percent of their market value. Consumer electronics and computer makers have long struggled in a world of exponential technology improvements and short product life spans. But until recently, hotels, taxi services, doctors, and energy companies had little to fear from the information revolution. Those days are gone forever. Software-based products are replacing physical goods. And every service provider must compete with cloud-based tools that offer customers a better way to interact. Today, start-ups with minimal experience and no capital can unravel your strategy before you even begin to grasp what’s happening. Never mind the “innovator’s dilemma”—this is the innovator’s disaster. And it’s happening in nearly every industry. Worse, Big Bang Disruptors may not even see you as competition. They don’t share your approach to customer service, and they’re not sizing up your product line to offer better prices. You may simply be collateral damage in their efforts to win completely different markets. The good news is that any business can master the strategy of the start-ups. Larry Downes and Paul Nunes analyze the origins, economics, and anatomy of Big Bang Disruption. They identify four key stages of the new innovation life cycle, helping you spot potential disruptors in time. And they offer twelve rules for defending your markets, launching disruptors of your own, and getting out while there’s still time. Based on extensive research by the Accenture Institute for High Performance and in-depth interviews with entrepreneurs, investors, and executives from more than thirty industries, Big Bang Disruption will arm you with strategies and insights to thrive in this brave new world.
There is an ongoing data explosion transpiring that will make previous creations, collections, and storage of data look trivial. Big Data, Mining, and Analytics: Components of Strategic Decision Making ties together big data, data mining, and analytics to explain how readers can leverage them to extract valuable insights from their data. Facilitating a clear understanding of big data, it supplies authoritative insights from expert contributors into leveraging data resources, including big data, to improve decision making. Illustrating basic approaches of business intelligence to the more complex methods of data and text mining, the book guides readers through the process of extracting valuable knowledge from the varieties of data currently being generated in the brick and mortar and internet environments. It considers the broad spectrum of analytics approaches for decision making, including dashboards, OLAP cubes, data mining, and text mining. Includes a foreword by Thomas H. Davenport, Distinguished Professor, Babson College; Fellow, MIT Center for Digital Business; and Co-Founder, International Institute for Analytics Introduces text mining and the transforming of unstructured data into useful information Examines real time wireless medical data acquisition for today’s healthcare and data mining challenges Presents the contributions of big data experts from academia and industry, including SAS Highlights the most exciting emerging technologies for big data—Hadoop is just the beginning Filled with examples that illustrate the value of analytics throughout, the book outlines a conceptual framework for data modeling that can help you immediately improve your own analytics and decision-making processes. It also provides in-depth coverage of analyzing unstructured data with text mining methods to supply you with the well-rounded understanding required to leverage your information assets into improved strategic decision making.

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