Over the last decade, we have been witnessing an increasing trend of Business Intelligence (BI) solutions leaving their traditional "boundaries" and moving toward the Web, either to source data from it or to expose a web-accessible interface on it (for both human and programmatic consumption). The goal of BI applications is to allow business people to query, understand, and analyze their business data in order to make better decisions. Traditionally, BI applications allowed business people to acquire insight into the data of their organization by means of a variety of technologies, such as data warehousing, data mining, business performance management, OLAP, periodical business reports, and the like. However, the recent evolutions are reshaping the technological landscape and the features provided by modern BI applications are changing.

This book aims to study and understand this dynamics and to reconcile two well-known research areas that come together in this new kind of web-enabled BI applications, i.e., Business Intelligence and Web Engineering. In particular, the book focuses on the following two aspects:

1. Data from the Web is feeding BI applications. BI applications no longer limit their analysis to the data inside one company. Increasingly, they also source their data from the outside, i.e., from the Web, and complement company-internal data with value-adding information from the Web (e.g., retail prices of products sold by competitors), in order to provide richer insights into the dynamics of today's business. The amount and complexity of the data available on the Web is growing rapidly. As a consequence, designers of BI applications making use of data from the Web have to deal with several issues. Many interesting research challenges arise when the Web is seen as data repository: Web warehousing models, data quality issues, integration of semantic Web technologies, Web mining technologies, BI with unstructured or semi-structured data, Web Intelligence methodologies or the application of Natural Language Processing (NLP) techniques to the BI field.
2. BI applications are moving to the Web. In parallel to the move of data from the Web into BI applications, we are also assisting to the move of BI applications from company-internal information systems to the Web: BI as a service (e.g., hosted BI platforms for small- and medium-size companies) is the target of huge investments and the focus of large research efforts by industry. The idea is that of outsourcing the processing and analysis of large bodies of data and consuming BI from the cloud. The move of BI applications from company-internal information systems to applications that are accessible over the Web implies the need for web-specific design competencies. In this context, research is focused on using Web engineering methodologies and technologies in BI: real-time BI and business performance management applications, Web mashups and RIA for BI development, usability and accessibility for BI applications, security issues in BI, and so on.

The aim of this book is to collect current works on how to leverage the huge amount of data that is available on the Web in BI applications, apply Web engineering methods and techniques to the design of BI applications, and use BI knowledge in the design of Web applications.