There are two remarkable phenomena that are unfolding almost simultaneously. The first is the emergence of a data-first world, where data has become a central driving force, shaping industries and fueling innovation. The second is the dawn of the AI age, propelled by the advent of Generative AI, that has created the possibility to leverage the data of the world for the first time. The convergence of these two, with data as the common denominator, holds immense promise and the opportunities are boundless. This book provides us with opportunities to push our thinking, to innovate, to transform and to create a better future at all levels—individual, enterprise and the world.

A "skillful and lucid" (The Wall Street Journal) way of thinking about efficiency, challenging our obsession with it—and offering a new understanding of how to benefit from the powerful potential of serendipity. Algorithms, multitasking, the sharing economy, life hacks: our culture can't get enough of efficiency. One of the great promises of the Internet and big data revolutions is the idea that we can improve the processes and routines of our work and personal lives to get more done in less time than we ever have before. There is no doubt that we're performing at higher levels and moving at unprecedented speed, but what if we're headed in the wrong direction? Melding the long-term history of technology with the latest headlines and findings of computer science and social science, The Efficiency Paradox questions our ingrained assumptions about efficiency, persuasively showing how relying on the algorithms of digital platforms can in fact lead to wasted efforts, missed opportunities, and, above all, an inability to break out of established patterns. Edward Tenner reveals what we and our institutions, when equipped with an astute combination of artificial intelligence and trained intuition, can learn from the random and unexpected.

With an emphasis on clarity, style, and performance, author J.T. Wolohan expertly guides you through implementing a functionally-influenced approach to Python coding. You'll get familiar with Python's functional built-ins like the functools operator and itertools modules, as well as the toolz library. Mastering Large Datasets teaches you to write easily readable, easily scalable Python code that can efficiently process large volumes of structured and unstructured data. By the end of this comprehensive guide, you'll have a solid grasp on the tools and methods that will take your code beyond the laptop and your data science career to the next level! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

The PR Paradox by Matias Rodsevich is a must-read for startups and scale-ups that are looking to establish and elevate their presence in the saturated tech market. Essentially "a public relations handbook", it is one of the best PR books and a complete guide on the creative foundation of their own PR strategy in a cost-effective and timely manner, to achieve growth-driven integrated solutions. The book offers exclusive insights into the modern PR practice, including tangible advice from renowned PR professionals, and provides real-time solutions on how to achieve significant PR results that will boost business growth in a cost and time effective manner. Unlike other PR books, The PR Paradox acts as a hands-on strategic guide for small businesses to achieve their goal implementing a practical and cost-effective PR strategy. Written for those who are interested in or just starting out in PR, the lessons and examples collected are both entertaining and informative. Readers can expect to take away from The PR Paradox key learnings that will give the initiate a leg up in the frantically paced world of PR.

The practical handbook for understanding and winning in the post-COVID digital age and becoming a 21st century leader. For every enterprise and its leaders, the digital age is a roller-coaster ride with more than its fair share of thrills and spills. It presents them with great opportunities to leapfrog and grow. However, success is not easy in the Digital Age. It requires a complete overhaul of the business model and organizational design, and the mind-sets of professionals. Such a large and complex change is not easy to manage, and enterprises often lose their way in their digital transformation attempts. Nitin brings in this book his 25+ years of experience in leadership roles in world-class firms like Mckinsey and Fidelity and Digital natives like Flipkart and Incedo. He presents compelling insights and practical examples and answers key questions on how enterprises can win in the Digital Age: • Why do firms fail at digital transformation? • How are the rules of business changing in the digital age? What disruptive opportunities does digital present in various industries? • How to best leverage the potential of digital technologies like AI and the Cloud? • How do organizational capabilities and culture need to change? • What new skills do leaders and young professionals need to build? Nitin brings clarity to the transformation process, breaking it down into seven building blocks and presenting how best to master them. The book is a practitioner’s guide for people across all age groups - students, young professionals, experienced professionals, senior executives on how they can realize the amazing opportunities the digital age offers them and achieve their true potential at work and in personal life.

Drawing lessons from one of the best models of success, the evolutionary model, this book explains why an organization must actively monitor the market environment and competitors to ascertain excellence and reconfigure and reframe continuously. It introduces the patterns and anti-patterns of excellence and includes detailed case studies based on different variations, including structure variations, shared values variations, and staff variations. The book includes case history segments from Toyota, Acer, eBay, Cisco, Blackberry, Samsung, Volvo, Charles Schwab, McDonalds, Starbucks, Google, Disney, and NUMMI; as well as detailed case histories of GE, IBM, and UPS.

Why healthcare cannot—and should not—become data-driven, despite the many promises of intensified data sourcing. In contemporary healthcare, everybody seems to want more data, of higher quality, on more people, and to use this data for a wider range of purposes. In theory, such pervasive data collection should lead to a healthcare system in which data can quickly, efficiently, and unambiguously be interpreted and provide better care for patients, more efficient administration, enhanced options for research, and accelerated economic growth. In practice, however, data are difficult to interpret and the many purposes often undermine one another. In this book, anthropologist and STS scholar Klaus Hoeyer offers an in-depth look at the paradoxes surrounding healthcare data. Focusing on Denmark, a world leader in healthcare data infrastructures, Hoeyer shares the perspectives of different stakeholders, from epidemiologists to hospital managers, from patients to physicians, analyzing the social dynamics set in motion by data intensification and calling special attention to that which cannot be easily coded in a database. HHe illustrates how data can be at once helpful, overwhelming, and sometimes disastrous through concrete examples. The COVID-19 pandemic serves as a special closing case study that shows how these data paradoxes carry weighty political implications. By revealing the diverse and sometimes contradictory practices spawned by intensified data sourcing, Data Paradoxes raises vital questions about how we might better use healthcare data.

The key to a successful MDM initiative isn't technology or methods, it's people: the stakeholders in the organization and their complex ownership of the data that the initiative will affect.Master Data Management equips you with a deeply practical, business-focused way of thinking about MDM—an understanding that will greatly enhance your ability to communicate with stakeholders and win their support. Moreover, it will help you deserve their support: you'll master all the details involved in planning and executing an MDM project that leads to measurable improvements in business productivity and effectiveness. - Presents a comprehensive roadmap that you can adapt to any MDM project - Emphasizes the critical goal of maintaining and improving data quality - Provides guidelines for determining which data to "master. - Examines special issues relating to master data metadata - Considers a range of MDM architectural styles - Covers the synchronization of master data across the application infrastructure

A cutting-edge response to Ralph Kimball's challenge to thedata warehouse community that answers some tough questions aboutthe effectiveness of the relational approach to datawarehousing Written by one of the best-known exponents of the Bill Inmonapproach to data warehousing Addresses head-on the tough issues raised by Kimball andexplains how to choose the best modeling technique for solvingcommon data warehouse design problems Weighs the pros and cons of relational vs. dimensional modelingtechniques Focuses on tough modeling problems, including creating andmaintaining keys and modeling calendars, hierarchies, transactions,and data quality

Overview This diploma course covers all aspects you need to know to become a successful Data Scientist. Content - Getting Started with Data Science - Data Analytic Thinking - Business Problems and Data Science Solutions - Introduction to Predictive Modeling: From Correlation to Supervised Segmentation - Fitting a Model to Data - Overfitting and Its Avoidance - Similarity, Neighbors, and Clusters Decision Analytic Thinking I: What Is a Good Model? - Visualizing Model Performance - Evidence and Probabilities - Representing and Mining Text - Decision Analytic Thinking II: Toward Analytical Engineering - Other Data Science Tasks and Techniques - Data Science and Business Strategy - Machine Learning: Learning from Data with Your Machine. - And much more Duration 6 months Assessment The assessment will take place on the basis of one assignment at the end of the course. Tell us when you feel ready to take the exam and we’ll send you the assignment questions. Study material The study material will be provided in separate files by email / download link.