Data Warehouses and OLAP: Concepts, Architectures, and SolutionsRobert Wrembel, Christian Koncilia Idea Group Inc (IGI), 1 sty 2007 - 332 Data warehouses and online analytical processing (OLAP) are emerging key technologies for enterprise decision support systems. They provide sophisticated technologies from data integration, data collection and retrieval, query optimization, and data analysis to advanced user interfaces. New research and technological achievements in the area of data warehousing are implemented in commercial database management systems, and organizations are developing data warehouse systems into their information system infrastructures. Data Warehouses and OLAP: Concepts, Architectures and Solutions covers a wide range of technical, technological, and research issues. It provides theoretical frameworks, presents challenges and their possible solutions, and examines the latest empirical research findings in the area. It is a resource of possible solutions and technologies that can be applied when designing, implementing, and deploying a data warehouse, and assists in the dissemination of knowledge in this field. |
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Spis treści
Conceptual Modeling Solutions for the Data Warehouse | 1 |
Handling Structural Heterogeneity in OLAP | 27 |
Data QualityBased Requirements Elicitation for Decision Support Systems | 58 |
Loading and Refreshing | 87 |
Extraction Transformation and Loading Processes | 88 |
Data Warehouse Refreshment | 111 |
Efficiency of Analytical Processing | 135 |
Advanced Ad Hoc Star Query Processing | 136 |
Efficient and Robust NodePartitioned Data Warehouses | 203 |
OLAP with a Database Cluster | 230 |
Toward Integrating Data Warehousing with Data Mining Techniques | 253 |
Temporal Semistructured Data Models and Data Warehouses | 277 |
Spatial Online Analytical Processing SOLAP Concepts Architectures and Solutions from a Geomatics Engineering Perspective | 298 |
About the Editors | 320 |
About the Authors | 321 |
| 328 | |
Bitmap Indices for Data Warehouses | 157 |
Indexing in Data Warehouses Bitmaps and Beyond | 179 |
Inne wydania - Wyświetl wszystko
Data Warehouses and OLAP: Concepts, Architectures and Solutions: Concepts ... Wrembel, Robert Ograniczony podgląd - 2006 |
Data Warehouses and OLAP: Concepts, Architectures, and Solutions Robert Wrembel Podgląd niedostępny - 2007 |
Kluczowe wyrazy i wyrażenia
aggregation algorithms analysis application approach bins bitmap index bits chapter compressed bitmap conceptual modeling context Copying or distributing Copyright data cubes data mining data model data quality data sources data warehouse data warehousing datasets DBMS defined dimension constraints dimension of Figure dimension tables distributing in print domain efficient electronic forms elements encoding Engineering ETL process ETL workflows evaluation example fact table forms without written functions graph h-surrogate heterogeneous hierarchy schema Idea Group Inc implementation International Conference join KSEQ lattice loading methodology multidimensional OLAP OLAP queries OLTP online analytical processing operations optimization parallel partitioning performance permission of Figure phase PMap print or electronic problem Proceedings proposed query processing range encoding REBSI replication represent requirements Retrieved rollup Sarawagi semistructured data SOLAP spatial data star queries stored strategies structure techniques transaction transformation tuples update Vassiliadis
Popularne fragmenty
Strona 318 - Shekhar, S., Lu, CT, Tan, X., Chawla, S., & Vatsavai, R. (2001). Map Cube: A visualization tool for spatial data warehouses. In H. Miller & J. Han (Eds.), Geographic data mining and knowledge discovery (pp.