Titlebook: Data Warehousing and Knowledge Discovery; 14th International C Alfredo Cuzzocrea,Umeshwar Dayal Conference proceedings 2012 Springer-Verlag

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Conference proceedings 2012ehouse and OLAP extensions, data warehouse performance and optimization, data mining and knowledge discovery techniques, data mining and knowledge discovery applications, pattern mining, data stream mining, data warehouse confidentiality and security, and distributed paradigms and algorithms.

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BPMN-Based Conceptual Modeling of ETL Processesrom the sources to a common repository. New applications, like for example, real-time data warehousing, require agile and flexible tools that allow BI users to take timely decisions based on extremely up-to-date data. This calls for new ETL tools able to adapt to constant changes and quickly produce

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Sprint Planning Optimization in Agile Data Warehouse Designations), and include a sprint planning phase that is critical to ensure the project success. Several factors impact on the optimality of a sprint plan, e.g., the estimated complexity, business value, and affinity of the elemental functionalities included in each sprint, which makes the planning prob

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A Case Study on Model-Driven Data Warehouse Developmentodel-Driven Architecture (MDA) to DW development. However, most of these approaches are not evaluated in practice. Therefore, we conducted an evaluation of the Multidimensional Model-Driven Architecture (MD²A), based on a case study derived from a real-world DW project. The case study results can be

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Integrating ETL Processes from Information Requirementsg a DW system from a set of information sources is realized with extract-transform-load (ETL) processes based on SLAs and BLOs. The entire task is complex, time consuming, and hard to be performed manually. This paper presents our approach to the requirement-driven creation of ETL designs. Each requ

OWL

Automatic Transformation of Multi-dimensional Web Tables into Data Cubes from data cubes. In this paper, we develop a scheme that does the reverse transformation, automatically, so that one may produce charts directly from multi-dimensional tables using standard OLAP data visualization tools. In the process, we develop several new techniques for table processing: (i) ex

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