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...

"This book combines the latest empirical research findings, best practices, and applicable theoretical frameworks surrounding data analytics and knowledge acquisition while providing a multi-disciplinary perspective of the subject area"--Provided by publisher.