This comprehensive edited volume is the first of its kind, designed to serve as a textbook for long-duration business analytics programs. It can also be used as a guide to the field by practitioners. The book has contributions from experts in top universities and industry. The editors have taken extreme care to ensure continuity across the chapters...
Just how strong is the movement of big data analytics to the cloud? This report, based on a survey by O'Reilly data analyst John King, reveals that the desire among corporations to adopt big data-as-a-service is gaining momentum-and that many organizations with big data cloud experience are likely to expand their use.
King's recent sur...
The entertainment industry has long been dominated by legendary screenwriter William Goldman’s “Nobody-Knows-Anything” mantra, which argues that success is the result of managerial intuition and instinct. This book builds the case that combining such intuition with data analytics and rigorous scholarly knowledge provides a source of sustainab...
This book sheds new light on a selection of big data scenarios from an interdisciplinary perspective. It features legal, sociological and economic approaches to fundamental big data topics such as privacy, data quality and the ECJ's Safe Harbor decision on the one hand, and practical applications such as smart cars, wearables and web tracking ...
This project was initiated in 2009 with the aim to spread knowledge about mobile technologies and encourage people to enter our community or deepen their existing knowledge.
More than twenty writers from the mobile community share their know-how in dealing with topics such as accessibility in mobile apps, UX design, mobile analytics, prototyping...
A modern web-marketing book that outlines a multi-modal system for growing a website with SEO, Google AdWords/Facebook Ads, Conversion Optimisation, Copywriting/Classic Persuasion/Behavioural Psychology, Google Analytics, Statistical Significance, Email Marketing, and Remarketing. When I launched my first web application it started off with zero tr...
When running a web application or service, there are three crucial elements to keep tabs on: availability, performance, and usage. A wide variety of technologies are available to monitor these things, but one that stands apart is Application Insights, a developer tool available through the Microsoft Azure cloud platform. In Application Insights Suc...
The emergence of the Internet of Things (IoT), combined with greater heterogeneity not only online in cloud computing architectures but across the cloud-to-edge continuum, is introducing new challenges for managing applications and infrastructure across this continuum. The scale and complexity is simply so complex that it is no longer realistic for...
Build your database management knowledge with the technical open book, Introducing SQL Server 2016. Get an overview of the SQL Server 2016 features - from in-memory performance and enhanced security to end-to-end mobile business intelligence and advanced analytics.
Learn about faster queries, improved security, higher availability, and state-of-...
Inventory Analytics provides a comprehensive and accessible introduction to the theory and practice of inventory control - a significant research area central to supply chain planning. The book outlines the foundations of inventory systems and surveys prescriptive analytics models for deterministic inventory control. It further discusses predictive...
This third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. The ebook presents an overview of modern data science theory and princ...
Over the past decades, rapid developments in digital and sensing technologies, such as the Cloud, Web and Internet of Things, have dramatically changed the way we live and work. The digital transformation is revolutionizing our ability to monitor our planet and transforming the way we access, process and exploit Earth Observation data from satell...
Learn to design, implement, measure, and improve DevOps programs that are tailored to your organization. This concise guide assists leaders who are accountable for the rapid development of high-quality software applications.
In DevOps for Digital Leaders, deep collective experience on both sides of the dev - ops divide informs the global thought l...
Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide, developers and data scientists will discover how graph analytics deliver value, whether they're used for building dynamic network models or forecasting real-world ...
Focusing on recent advances in analytical techniques, this third edition of Andrew Duchowski’s successful guide has been revised and extended. It includes new chapters on calibration accuracy, precision and correction; advanced eye movement analysis; binocular eye movement analysis; practical gaze analytics; eye movement synthesis. Eye Tracking ...
This book considers all aspects of managing the complexity of Multimedia Big Data Computing (MMBD) for IoT applications and develops a comprehensive taxonomy. It also discusses a process model that addresses a number of research challenges associated with MMBD, such as scalability, accessibility, reliability, heterogeneity, and Quality of Service (...
This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual...
R is one of the most popular, powerful data analytics languages and environments in use by data scientists. Actionable business data is often stored in Relational Database Management Systems (RDBMS), and one of the most widely used RDBMS is Microsoft SQL Server. Much more than a database server, it's a rich ecostructure with advanced analytic ...
The processes for gathering, organizing, analyzing, and ultimately infusing AI throughout your organization can be thought of as a ladder. A ladder helps you climb far higher than you could go on your own by turning an impossible leap into a series of steps. Knowing what the ladder looks like helps you evaluate your organization's readiness fo...
Today we are witnessing an increased use of data visualization in society. Across domains such as work, education and the news, various forms of graphs, charts and maps are used to explain, convince and tell stories. In an era in which more and more data are produced and circulated digitally, and digital tools make visualization production increasi...
Power BI is a cloud-based business analytics service that gives us a single view of the most critical business data. A tool for creating live dashboards and rich, interactive reports, Power BI allows access to data for monitoring the health of a business. Pierstefano Tucci will take readers through the Power BI interface, query creation, publishing...
In this lively and approachable volume based on his popular blog series, Martin Weller demonstrates a rich history of innovation and effective implementation of ed tech across higher education. From Bulletin Board Systems to blockchain, Weller follows the trajectory of education by focusing each chapter on a technology, theory, or concept that has ...
Perform fast interactive analytics against different data sources using the Presto high-performance, distributed SQL query engine. With this practical guide, you'll learn how to conduct analytics on data where it lives, whether it's Hive, Cassandra, a relational database, or a proprietary data store. Analysts, software engineers, and prod...
Is Kubernetes ready for stateful workloads? This open source system has become the primary platform for deploying and managing cloud native applications. But because it was originally designed for stateless workloads, working with data on Kubernetes has been challenging. If you want to avoid the inefficiencies and duplicative costs of having separa...
This book proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS - Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, October 23-24, 2018. Cyber Physical Systems are characterized by their ability to...
"This book could well be the most comprehensive collection to date of integrated ideas on the elicitation, representation, integration and digitization of work processes and collaboration. The authors take a heavily human-centered approach while never losing sight of engineering aspects involved. Rooted in relevant theories, they present a set...
This open access Pivot demonstrates how a variety of technologies act as innovation catalysts within the banking and financial services sector. Traditional banks and financial services are under increasing competition from global IT companies such as Google, Apple, Amazon and PayPal whilst facing pressure from investors to reduce costs, increase ag...
It covers aspects of unsupervised machine learning used for knowledge discovery in data science and introduces a data-driven approach to cluster analysis, the Databionic swarm(DBS). DBS consists of the 3D landscape visualization and clustering of data. The 3D landscape enables 3D printing of high-dimensional data structures.The clustering and numbe...
In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be...
This book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using tec...
Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, cla...
The overarching aim of this book is to present self-contained theory and algorithms for investigation and prediction of electric demand peaks. A cross-section of popular demand forecasting algorithms from statistics, machine learning and mathematics is presented, followed by extreme value theory techniques with examples.In order to achieve carbon t...