Epidemic trend analysis, timeline progression, prediction, and recommendation are critical for initiating effective public health control strategies, and AI and data analytics play an important role in epidemiology, diagnostic, and clinical fronts. The focus of this book is data analytics for COVID-19, which includes an overview of COVID-19 in terms of epidemic/pandemic, data processing and knowledge extraction. Data sources, storage and platforms are discussed along with discussions on data models, their performance, different big data techniques, tools and technologies. This book also addresses the challenges in applying analytics to pandemic scenarios, case studies and control strategies. Aimed at Data Analysts, Epidemiologists and associated researchers, this book: discusses challenges of AI model for big data analytics in pandemic scenarios; explains how different big data analytics techniques can be implemented; provides a set of recommendations to minimize infection rate of COVID-19; summarizes various techniques of data processing and knowledge extraction; enables users to understand big data analytics techniques required for prediction purposes.
|Author||: Wolfgang Wörndl|
|Publisher||: Springer Nature|
|ISBN 10||: 303065785X|
|Pages||: 329 pages|
|Author||: Aboul-Ella Hassanien,Nilanjan Dey,Sally Elghamrawy|
|Publisher||: Springer Nature|
|Release Date||: 2020-11-13|
|ISBN 10||: 3030552586|
|Pages||: 307 pages|
This book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. In the context of COVID-19, this book focuses on how big data analytic and artificial intelligence help fight COVID-19. The book is divided into four parts. The first part discusses the forecasting and visualization of the COVID-19 data. The second part describes applications of artificial intelligence in the COVID-19 diagnosis of chest X-Ray imaging. The third part discusses the insights of artificial intelligence to stop spread of COVID-19, while the last part presents deep learning and big data analytics which help fight the COVID-19.
|Author||: Khalid Raza|
|Publisher||: Springer Nature|
|ISBN 10||: 9811585342|
|Pages||: 329 pages|
|Author||: Patil, Bhushan,Vohra, Manisha|
|Publisher||: IGI Global|
|Release Date||: 2020-10-23|
|ISBN 10||: 1799830543|
|Pages||: 583 pages|
Analyzing data sets has continued to be an invaluable application for numerous industries. By combining different algorithms, technologies, and systems used to extract information from data and solve complex problems, various sectors have reached new heights and have changed our world for the better. The Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics is a collection of innovative research on the methods and applications of data analytics. While highlighting topics including artificial intelligence, data security, and information systems, this book is ideally designed for researchers, data analysts, data scientists, healthcare administrators, executives, managers, engineers, IT consultants, academicians, and students interested in the potential of data application technologies.
Good data analytics is the basis for effective decisions. Whoever has the data, has the ability to extract information promptly and effectively to make pertinent decisions. The premise of this handbook is to empower users and tool developers with the appropriate collection of formulas and techniques for data analytics and to serve as a quick reference to keep pertinent formulas within fingertip reach of readers. This handbook includes formulas that will appeal to mathematically inclined readers. It discusses how to use data analytics to improve decision-making and is ideal for those new to using data analytics to show how to expand their usage horizon. It provides quantitative techniques for modeling pandemics, such as COVID-19. It also adds to the suite of mathematical tools for emerging technical areas. This handbook is a handy reference for researchers, practitioners, educators, and students in areas such as industrial engineering, production engineering, project management, civil engineering, mechanical engineering, technology management, and business management worldwide.
Data is bigger, arrives faster, and comes in a variety of formats—and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark. Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, you’ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow
|Author||: Gitanjali Rahul Shinde|
|Release Date||: 2020-11|
|ISBN 10||: 9780367564957|
|Pages||: 329 pages|
"Epidemic trend analysis, timeline progression, prediction and recommendation are critical for initiating effective public health control strategies and AI and data analytics play an important role in epidemiology, diagnostic and clinical fronts. The focus of this book is data analytics for COVID-19 which includes an overview of COVID-19 in terms of epidemic/pandemic, data processing and knowledge extraction. Data sources, storage and platforms are discussed along with discussion on data models, their performance, different Big data techniques, tools and technologies. This book also addresses the challenges in applying analytics to pandemic scenarios, case studies and control strategies"--
Discover powerful hidden social "levers" and networks within your company… then, use that knowledge to make slight "tweaks" that dramatically improve both business performance and employee fulfillment! In People Analytics, MIT Media Lab innovator Ben Waber shows how sensors and analytics can give you an unprecedented understanding of how your people work and collaborate, and actionable insights for building a more effective, productive, and positive organization. Through cutting-edge case studies, Waber shows how: Changing the way call center employees spent their breaks increased performance by 25% while significantly reducing stress Quantifying the failure of marketing and customer service to communicate led to a more cohesive and profitable organization Tweaking the balance of in-person and electronic communication can enhance the value of both Sensor data can help you discover who your internal experts really are Identifying employees involved in "creative" behaviors can help you promote innovation throughout your business Sensors and simulations can help you optimize your sick-day policies Measuring informal interactions can improve the chances that a merger, acquisition, or "mega-project" will succeed Drawing on his cutting-edge work at MIT and Harvard, Waber addresses crucial issues ranging from technology to privacy, revealing what will be possible in a few years, and what you can achieve right now. In bringing the power of analytics to organizational development, he offers immense new opportunities to everyone with responsibility for workplace performance.
|Author||: Harvard Business Review|
|Publisher||: Harvard Business Press|
|Release Date||: 2020-07-28|
|ISBN 10||: 1647820502|
|Pages||: 192 pages|
Lead through the crisis and prepare for recovery. As the Covid-19 pandemic is exacting its toll on the global economy, forward-looking organizations are moving past crisis management and positioning themselves to leap ahead when the worst is over. What should you and your organization be doing now to address today's unprecedented challenges while laying the foundation needed to emerge stronger? Coronavirus: Leadership and Recovery provides you with essential thinking about managing your company through the pandemic, keeping your employees (and yourself) healthy and productive, and spurring your business to continue innovating and reinventing itself ahead of the recovery. Business is changing. Will you adapt or be left behind? Get up to speed and deepen your understanding of the topics that are shaping your company's future with the Insights You Need from Harvard Business Review series. Featuring HBR's smartest thinking on fast-moving issues—blockchain, cybersecurity, AI, and more—each book provides the foundational introduction and practical case studies your organization needs to compete today and collects the best research, interviews, and analysis to get it ready for tomorrow. You can't afford to ignore how these issues will transform the landscape of business and society. The Insights You Need series will help you grasp these critical ideas—and prepare you and your company for the future.
THE NEW YORK TIMES BESTSELLER AN ECONOMIST BOOK OF THE YEAR A NEW STATESMAN BOOK OF THE YEAR 'This book is about a whole new way of studying the mind ... Endlessly fascinating' Steven Pinker 'A whirlwind tour of the modern human psyche' Economist Everybody lies, to friends, lovers, doctors, pollsters – and to themselves. In Internet searches, however, people confess the truth. Insightful, funny and always surprising, Everybody Lies explores how this huge collection of data, unprecedented in human history, could just be the most important ever collected. It offers astonishing insights into the human psyche, revealing the biases deeply embedded within us, the questions we're afraid to ask that might be essential to our well-being, and the information we can use to change our culture for the better.
Trust Creating the Foundation for Entrepreneurship in Developing Countries Entrepreneurial ventures often fail in the developing world because of the lack of something taken for granted in the developed world: trust. Over centuries the developed world has built up customs and institutions like enforceable contracts, an impartial legal system, credible regulatory bodies, even unofficial but respected sources of information like Yelp or Consumer Reports that have created a high level of what scholar and entrepreneur Tarun Khanna calls “ambient trust.” If a product is FDA-approved we feel confident it's safe. If someone makes an untrue claim or breaks an agreement we can sue. Police don't demand bribes to do their jobs. Certainly there are exceptions, but when brought to light they provoke a scandal, not a shrug. This is not the case in the developing world. But rather than become casualties of mistrust, Khanna shows that smart entrepreneurs adopt the mindset that, like it or not, it's up to them to weave their own independent web of trust—with their employees, their partners, their clients, their customers and with society as a whole. This can certainly be challenging, and requires innovative approaches in places where the level of societal mistrust is so high that, as in one example Khanna provides, an official certification of quality simply arouses suspicion—and lowers sales! Using vivid examples from Brazil, China, India, Mexico and elsewhere, Khanna shows how entrepreneurs can build on existing customs and practices instead of trying to push against them. He highlights the role new technologies can play (but cautions that these are not panaceas), and explains how entrepreneurs can find dependable partners in national and local governments to create impact at scale. As far back as the 18th century Adam Smith recognized trust as what Khanna calls “the hidden engine of economic progress.” “Frankness and openness conciliate confidence,” Smith wrote. “We trust the man who seems willing to trust us.” That kind of confidence is critical to entrepreneurial success, but in the developing world entrepreneurs have to establish it through their own efforts. As Khanna puts it, “the entrepreneur must not just create, she must create the conditions to create.”
Developing and implementing a systematic analytics strategy can result in a sustainable competitive advantage within the sport business industry. This timely and relevant book provides practical strategies to collect data and then convert that data into meaningful, value-added information and actionable insights. Its primary objective is to help sport business organizations utilize data-driven decision-making to generate optimal revenue from such areas as ticket sales and corporate partnerships. To that end, the book includes in-depth case studies from such leading sports organizations as the Orlando Magic, Tampa Bay Buccaneers, Duke University, and the Aspire Group. The core purpose of sport business analytics is to convert raw data into information that enables sport business professionals to make strategic business decisions that result in improved company financial performance and a measurable and sustainable competitive advantage. Readers will learn about the role of big data and analytics in: Ticket pricing Season ticket member retention Fan engagement Sponsorship valuation Customer relationship management Digital marketing Market research Data visualization. This book examines changes in the ticketing marketplace and spotlights innovative ticketing strategies used in various sport organizations. It shows how to engage fans with social media and digital analytics, presents techniques to analyze engagement and marketing strategies, and explains how to utilize analytics to leverage fan engagement to enhance revenue for sport organizations. Filled with insightful case studies, this book benefits both sports business professionals and students. The concluding chapter on teaching sport analytics further enhances its value to academics.
Do you wonder why some ideas go viral and others sink? Why one political candidate soars while another fails to gain traction? Why one product becomes an instant rage, while its competitor struggles to stay above water? What is the secret to momentum? Many people believe that momentum is driven by emotion and is unpredictable, but as Mike Berland, the internationally recognized pollster and strategic advisor, has discovered, it’s actually a science, with easily analyzed metrics. In Maximum Momentum: How to Get It, How to Keep It, Berland reveals the key to momentum, beginning with the simple physics formula— mass x velocity. He then develops a Momentum Matrix—five signals that decode the science into effective measures. Maximum Momentum is a lively examination of hot trends in the current arena—from politics to society to business to sports. Using colorful graphics to underscore the stories, Berland examines the people, issues, movements and products that most captivate Americans.
A comprehensive collection of the field's most provocative, influential new work Business Forecasting compiles some of the field's important and influential literature into a single, comprehensive reference for forecast modeling and process improvement. It is packed with provocative ideas from forecasting researchers and practitioners, on topics including accuracy metrics, benchmarking, modeling of problem data, and overcoming dysfunctional behaviors. Its coverage includes often-overlooked issues at the forefront of research, such as uncertainty, randomness, and forecastability, as well as emerging areas like data mining for forecasting. The articles present critical analysis of current practices and consideration of new ideas. With a mix of formal, rigorous pieces and brief introductory chapters, the book provides practitioners with a comprehensive examination of the current state of the business forecasting field. Forecasting performance is ultimately limited by the 'forecastability' of the data. Yet failing to recognize this, many organizations continue to squander resources pursuing unachievable levels of accuracy. This book provides a wealth of ideas for improving all aspects of the process, including the avoidance of wasted efforts that fail to improve (or even harm) forecast accuracy. Analyzes the most prominent issues in business forecasting Investigates emerging approaches and new methods of analysis Combines forecasts to improve accuracy Utilizes Forecast Value Added to identify process inefficiency The business environment is evolving, and forecasting methods must evolve alongside it. This compilation delivers an array of new tools and research that can enable more efficient processes and more accurate results. Business Forecasting provides an expert's-eye view of the field's latest developments to help you achieve your desired business outcomes.
|Author||: Aboul Ella Hassanien,Roheet Bhatnagar,Ashraf Darwish|
|Publisher||: Springer Nature|
|Release Date||: 2020-08-31|
|ISBN 10||: 3030519201|
|Pages||: 311 pages|
This book highlights the latest advances in the field of artificial intelligence and related technologies, with a special focus on sustainable development and environmentally friendly artificial intelligence applications. Discussing theory, applications and research, it covers all aspects of artificial intelligence in the context of sustainable development.
|Author||: Amit Joshi|
|Publisher||: Springer Nature|
|ISBN 10||: 9811565724|
|Pages||: 329 pages|
|Author||: Tim Menzies,Laurie Williams,Thomas Zimmermann|
|Publisher||: Morgan Kaufmann|
|Release Date||: 2016-07-14|
|ISBN 10||: 0128042613|
|Pages||: 408 pages|
Perspectives on Data Science for Software Engineering presents the best practices of seasoned data miners in software engineering. The idea for this book was created during the 2014 conference at Dagstuhl, an invitation-only gathering of leading computer scientists who meet to identify and discuss cutting-edge informatics topics. At the 2014 conference, the concept of how to transfer the knowledge of experts from seasoned software engineers and data scientists to newcomers in the field highlighted many discussions. While there are many books covering data mining and software engineering basics, they present only the fundamentals and lack the perspective that comes from real-world experience. This book offers unique insights into the wisdom of the community’s leaders gathered to share hard-won lessons from the trenches. Ideas are presented in digestible chapters designed to be applicable across many domains. Topics included cover data collection, data sharing, data mining, and how to utilize these techniques in successful software projects. Newcomers to software engineering data science will learn the tips and tricks of the trade, while more experienced data scientists will benefit from war stories that show what traps to avoid. Presents the wisdom of community experts, derived from a summit on software analytics Provides contributed chapters that share discrete ideas and technique from the trenches Covers top areas of concern, including mining security and social data, data visualization, and cloud-based data Presented in clear chapters designed to be applicable across many domains
Tomorrow’s customers need to be targeted today! With emerging technology transforming customer expectations, it’s more important than ever to keep a laser focus on the experience companies provide their customers. In The Customer of the Future, customer experience futurist Blake Morgan outlines ten easy-to-follow customer experience guidelines that integrate emerging technologies with effective strategies to combat disconnected processes, silo mentalities, and a lack of buyer perspective. Tomorrow’s customers will insist on experiences that make their lives significantly easier and better. Companies will win their business not by just proclaiming that customer experience is a priority but by embedding a customer focus into every aspect of their operations. They’ll understand how emerging technologies like artificial intelligence (AI), automation, and analytics are changing the game and craft a strategy to integrate them into their products and processes. The Customer of the Future explains how today’s customers are already demanding frictionless, personalized, on-demand experiences from their products and services, and companies that don’t adapt to these new expectations won’t last. This book prepares your organization for these increasing demands by helping you do the following: Learn the ten defining strategies for a customer experience–focused company. Implement new techniques to shift the entire company from being product-focused to being customer-focused. Gain insights through case studies and examples on how the world’s most innovative companies are offering new and compelling customer experiences. Craft a leadership development and culture plan to create lasting change at your organization.
|Author||: Krishna Kumar Mohbey,Arvind Pandey,Dharmendra Singh Rajput|
|Publisher||: Bentham Science Publishers|
|Release Date||: 2020-12-09|
|ISBN 10||: 9811490511|
|Pages||: 124 pages|
This book presents a selection of the latest and representative developments in predictive analytics using big data technologies. It focuses on some critical aspects of big data and machine learning and provides studies for readers. The chapters address a comprehensive range of advanced data technologies used for statistical modeling towards predictive analytics. Topics included in this book include: - Categorized machine learning algorithms - Player monopoly in cricket teams. - Chain type estimators - Log type estimators - Bivariate survival data using shared inverse Gaussian frailty models - Weblog analysis - COVID-19 epidemiology This reference book will be of significant benefit to the predictive analytics community as a useful guide of the latest research in this emerging field.