Bøker i Data Analytics Applications-serien

Data has reshaped industries around the world, from finance and medicine to sports. Law has trailed behind other industries, but is quickly following suit. For many years, law firms made important decisions ¿ including very large decisions ¿ based on limited experience (at best), or hunches (at worst). Data science is growing quickly in law firms, law schools, and corporate legal departments. Sophisticated clients not only prefer firms that use data analysis in their practice ¿ they soon will demand it. In Data Analytics Applications in Law, leading practitioners examine the cutting edge of this trend, looking at new tools from our present, as well as the future of data analytics in law.

This book gives a comprehensive coverage of state-of-the-art big data analytics in cybersecurity and IT management. The topics include threat analysis, vulnerability identification, mission analysis, network monitoring, network management, visualization, and cybertraining. Each topic is examined in detail in a case study.

In education, big data analytics is being used to enhance the learning process, evaluate efficiency, improve feedback, and enrich the learning experience. Integrating data from different institutions enables data-driven decision-making. This book presents innovative applications of data analytics in primary, secondary, and tertiary education.

This books sheds light on the unique and creative contributions that the arts and humanities can make to the development of approaches to effectively use big data. It also looks at opportunities and challenges for research in the arts and humanities created by the capability to handle and use sophisticatedly very huge and complex data sets.

Data has reshaped industries around the world, from finance and medicine to sports. Law has trailed behind other industries, but is quickly following suit. For many years, law firms made important decisions - including very large decisions - based on limited experience (at best), or hunches (at worst). Data science is growing quickly in law firm

This book aims to help the reader better understand the importance of data analysis in project management. Moreover, it provides guidance by showing tools, methods, techniques and lessons learned on how to better utilize the data gathered from the projects.

Effective presentation of analytical results is the key to close a project successfully. With the meteoric rise in the popularity of data science and analytics, business executives focus on analytics' strategic interpretation and managerial implications, as well as value creation from analytics.

Innovation based in data analytics is a contemporary approach to developing empirically supported advances that encourage entrepreneurial activity inspired by novel marketing inferences. Data Analytics in Marketing, Entrepreneurship, and Innovation covers techniques, processes, models, tools, and practices for creating business opportunities through data analytics. It features case studies that provide realistic examples of applications. This multifaceted examination of data analytics looks at: Business analyticsApplying predictive analytics Using discrete choice analysis for decision-making Marketing and customer analyticsDeveloping new productsTechnopreneurshipDisruptive versus incremental innovationThe book gives researchers and practitioners insight into how data analytics is used in the areas of innovation, entrepreneurship, and marketing. Innovation analytics helps identify opportunities to develop new products and services, and improve existing methods of product manufacturing and service delivery. Entrepreneurial analytics facilitates the transformation of innovative ideas into strategy and helps entrepreneurs make critical decisions based on data-driven techniques. Marketing analytics is used in collecting, managing, assessing, and analyzing marketing data to predict trends, investigate customer preferences, and launch campaigns.

Parents are questioning the value of virtual learning. A way to address such doubts is learning analytics. This book focuses on how learning analytics can measure student e-learning outcomes. Insight from academia, industry, and not-for-profit organizations demonstrate how learning analytics can determine the pros and cons of e-learning.

Parents are questioning the value of virtual learning. A way to address such doubts is learning analytics. This book focuses on how learning analytics can measure student e-learning outcomes. Insight from academia, industry, and not-for-profit organizations demonstrate how learning analytics can determine the pros and cons of e-learning.

Focusing on important aspects of analytics that facilitate innovation, promote entrepreneurship, and improve marketing efficiency and effectiveness, this book provides researchers and business practitioners insight on the techniques, tools, models, and cases of data analytics in the broad areas of innovation, entrepreneurship, and marketing.

This book aims to help the reader better understand the importance of data analysis in project management. Moreover, it provides guidance by showing tools, methods, techniques and lessons learned on how to better utilize the data gathered from the projects.

The book looks at the question: How well do executives trust their intuition? In other words, do they typically prefer intuition over analysis/analytics, and what types of intuition (Holistic-Big Picture, Holistic-Abstract, Affective Intuition, Inferential Intuition) may be most favorable looking at different variables?

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.

This books sheds light on the unique and creative contributions that the arts and humanities can make to the development of approaches to effectively use big data. It also looks at opportunities and challenges for research in the arts and humanities created by the capability to handle and use sophisticatedly very huge and complex data sets.

Scientific knowledge is doubling every 10 to 15 years worldwide. Who generates this knowledge? Where is this information stored? How is it being utilized? These are some issues addressed in this book on data analytics and scientometrics, which brings together scientific production, research evaluation, and reputation of world-class universities.

This book gives a comprehensive coverage of state-of-the-art big data analytics in cybersecurity and IT management. The topics include threat analysis, vulnerability identification, mission analysis, network monitoring, network management, visualization, and cybertraining. Each topic is examined in detail in a case study.

The application of big data and analytics (BDA) techniques can greatly enhance the efficiency of private-sector organizations. This book present case studies with academic and practitioner viewpoints on BDA in public-sector agencies. It covers the application of BDA technologies and techniques.

This book is about the application of analytics processes to organizations in Latin American and emerging economies. The selected cases illustrate the steps in the analytics knowledge process, including strategic and tactical actions. The book demonstrates that analytics is for organizations of any size and for developing markets.

The military produces, senses, and consumes a tremendous amount of data. Developing ways to effectively leverage these troves of data to enhance operations is a persistent goal. This book explores data analytics techniques that military scientists and practitioners around the world are doing to achieve this. The book is organized around data analytics applications in the primary military domains of personnel, intelligence, operations, and logistics.

This book presents and discusses the main challenges posed by big data and analytics in a manner relevant to both practitioners and scholars. The first part of the book describes the growing relevance of big data and analytics in gaining competitive advantage. The second part presents case studies emphasizing application.

Effective presentation of analytical results is the key to close a project successfully. With the meteoric rise in the popularity of data science and analytics, business executives focus on analytics' strategic interpretation and managerial implications, as well as value creation from analytics.

The purpose of this book is to show how high-growth enterprises create their business models. To illustrate the background of this topic, the concepts of business models existing in the literature are presented along with their perspective on further development and external conditions that affect them.