Get started with artificial intelligence in your business. This book will help you understand AI, its implications, and how to adopt a strategy that is rational, relevant, and practical. Beyond the buzzwords and the technology complexities, organizations are struggling to understand what AI means for their industry and how they can start their journey. How to Compete in the Age of Artificial Intelligence is not a book about complex formulas or solution architectures. It goes deeper into explaining the meaning and relevance of AI for your business. You will learn how to apply AI thinking across enterprise functions-including disruptive technologies such as IoT, Blockchain, and cloud-and transform your organization. What You'll Learn Know how to spot AI opportunities and establish the right organizational imperatives to grow your business Understand AI in the context of changing business dynamics and the workforce/skills required to succeed Discover how to apply AI thinking across enterprise functions-from the boardroom to cybersecurity, IoT, IT operations, policies-and implement a sustainable and integrated human-machine collaboration strategy Who This Book is For CxOs, senior executives, mid-level managers, AI evangelists, digital leads, and technology directors

Big Data Imperatives, focuses on resolving the key questions on every one'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. Your goal may be to obtain insight from voluminous data, with billions of loosely-structured bytes of data coming from different channels spread across different locations, which needs to be processed until the needle in the haystack is found.This book addresses the following big data characteristics: * Very large, distributed aggregations of loosely structured data -- often incomplete and inaccessible * Petabytes/Exabytes of data * Millions/billions of people providing/contributing to the context behind the data * Flat schema's with few complex interrelationships * Involves time-stamped events * Made up of incomplete data * Includes connections between data elements that must be probabilistically inferred Big data imperatives, explains 'what big data can do'. It can batch process millions and billions of records both unstructured and structured much faster and cheaper. Big data analytics provide a platform, to merge all analysis which enables data analysis to be more accurate, well-rounded, reliable and focused on a specific business capability. 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. What you'll learn * Understanding the technology, implementation of big data platforms and their usage for analytics * Big data architectures * Big data design patterns * Implementation best practices Who this book is for This book is designed for IT professionals, data warehousing, business intelligence professionals, data analysis professionals, architects, developers and business users