Recommendations for Your Data Visualization Bookshelf

Over the years that I’ve been involved in data visualization, I have collected a number of books on the topic. Not every book in my library is great, but a few stand out as particularly useful for businesspeople who wish to become experts in using visualizations to analyze and communicate quantitative data. I have intentionally not included most of the books that focus on the visualization needs of scientists and statisticians. A few books that venture in this direction have been included, however, because they provide a great deal of general content that is extremely worthwhile, such as those by Edward Tufte and William Cleveland. Fundamentals of Graph Design I will begin the list with those books that cover the fundamentals of graph design for the communication of quantitative business information. Even though it will appear self-promoting, I unapologetically recommend my own book, Show Me the Numbers: Designing Tables and Graphs to Enlighten, as the best available resource on the design of graphs (and tables) for communicating quantitative business information. As someone who has been involved in the business intelligence industry for many years, I am intimately aware of the needs of businesspeople who must make sense of quantitativ

Machine learning and deep learning

Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Machine learning describes the capacity of systems to learn from problem-specific training data to automate the process of analytical model building and solve associated tasks. Deep learning is a machine learning concept based on artificial neural networks. For many applications, deep learning models outperform shallow machine learning models and traditional data analysis approaches. In this article, we summarize the fundamentals of machine learning and deep learning to generate a broader understanding of the methodical underpinning of current intelligent systems. In particular, we provide a conceptual distinction between relevant terms and concepts, explain the process of automated analytical model building through machine learning and deep learning, and discuss the challenges that arise when implementing such intelligent systems in the field of electronic markets and networked business. These naturally go beyond technological aspects and highlight issues in human-machine interaction and artificial intelligence servitization.Comment: Published online first in Electronic Market

Demand driven web services

Web services are playing a pivotal role in e-business, service intelligence, and service science. Demand-driven web services are becoming important for web services and service computing. However, many fundamental issues are still ignored to some extent. For example, what is the demand theory for web services, what is a demand-driven architecture for web services and what is a demand-driven web service lifecycle remain open. This chapter addresses these issues by examining fundamentals for demand analysis in web services, and proposing a demand-driven architecture for web services. It also proposes a demand-driven web service lifecycle for the main players in web services: Service providers, service requestors and service brokers, respectively. It then provides a unified perspective on demand-driven web service lifecycles. The proposed approaches will facilitate research and development of web services, e-services, service intelligence, service science and service computing

Fundamentals of Earth Observation Policy: Examples for German and European Missions

Several European countries have developed their national high resolution earth observation systems. Some of them are operated in close cooperation with industrial partners, others are dual-use missions earmarked to fulfil the needs of national security. In addition, the European Space Agency and the European Commission have initiated the Global Monitoring for Environment and Security (GMES) project. Therein, a fleet of satellites (SENTINELs) will deliver data for European wide information services, augmented by data from national and non-European earth observation systems. This new scenario needs clear guidance and regulations. Besides the principles for operations of earth observation missions – as set out in UN principles on earth observation – the operators of very high resolution missions require clear governmental acts which international users can be served and which data might be restricted in distribution. For national science and the SENTINEL-missions, a policy for free and open access is being developed to guarantee a maximum use of the data. Exemplified on the German national missions and the European GMES scenario, data policies and regulations for existing and new earth observation missions will be explained

Border Security: Understanding Threats at U.S. Borders

[Excerpt] The United States confronts a wide array of threats at U.S. borders, ranging from terrorists who may have weapons of mass destruction, to transnational criminals smuggling drugs or counterfeit goods, to unauthorized migrants intending to live and work in the United States. Given this diversity of threats, how may Congress and the Department of Homeland Security (DHS) set border security priorities and allocate scarce enforcement resources? In general, DHS’s answer to this question is organized around risk management, a process that involves risk assessment and the allocation of resources based on a cost-benefit analysis. This report focuses on the first part of this process by identifying border threats and describing a framework for understanding risks at U.S. borders. DHS employs models to classify threats as relatively high- or low-risk for certain planning and budgeting exercises and to implement certain border security programs. Members of Congress may wish to use similar models to evaluate the costs and benefits of potential border security policies and to allocate border enforcement resources. This report discusses some of the issues involved in modeling border-related threats

Methods of presenting the fundamentals of bookkeeping

Thesis (Ed.M.)--Boston Universit