Due to their widespread use, Internet, Web 2.0 and digital sensors create data in non-traditional volumes (at terabytes and petabytes scale). The big data characterized by the four V's has brought with it new challenges given the limited capabilities of traditional computing systems. This paper...

In data warehousing, the data from source systems are populated into a central data warehouse (DW) through extraction, transformation and loading (ETL). The standard ETL approach usually uses sequential jobs to process the data with dependencies, such as dimension and fact data. It is a...

Data warehouses have become over the last two decades an essential element in the area of economic intelligence. Although the basic concepts related to this technology are now more standardized (multidimensional model, OLAP technology...), the design method issue remains in discussion, since no...

Business surveys indicate that fewer than 30% of data warehousing and business intelligence (DW/BI) projects meet the stated goals of the budget, schedule, and quality. Agile methods have been suggested as a possible solution, but because of the large size of the typical DW/BI project, it may be...

Machine generated contents note: Foreword Preface Acknowledgments Chapter 1 The Critical Role of Business Insight The Disruptive Nature of Data An Unconventional Look at Conventional "Wisdom" Innovating at the Speed of Data Weighing Risk and Bringing the Better Part of "Gut Instinct" Back into...

There are more than one billion documents on the Web, with the count continually rising at a pace of over one million new documents per day. As information increases, the motivation and interest in data warehousing and mining research and practice remains high in organizational interest. This...