01542    a2200157   4500020001500000040001300015100002000028245007300048260005200121300001900173440007100192520103400263650002201297650004701319700001801366  a013680604X  aDLCbDLC1 aMorse, Stephen,10aParallel systems in the data warehouse cStephen Morse, David Isaac.  aUpper Saddle River, NJ :bPrentice Hall,c1998.  a395 p. :bill. 4aThe Data Warehousing Institute series from Prentice Hall PTR ;v3.1 a"Discover why parallel computing offers an ideal foundation for enterprise-scale data warehousing - and how to make the right strategic and tactical decisions about these critical technologies."--BK JACKET. "What are the right questions to ask? What aren't the vendors telling you? How do benchmarks relate to real-world results? Parallel Systems in the Data Warehouse evaluates all three major parallel hardware architectures, comparing scalability, performance and sustainable I/O bandwidth: symmetric multiprocessors (SMP), distributed memory (DM) or "massively parallel" machines, and distributed shared memory (DSM) systems ("non-uniform memory access" machines)."--BK JACKET. "Consistently high throughput is critical to the success of data warehousing - and traditional techniques like normalization and indexing aren't enough anymore. Learn smarter table partitioning strategies, star schema and other powerful techniques to fully exploit the inherent scalability and high I/O bandwidth of parallel hardware."--BK JACKET. 0aData warehousing. 0aParallel processing (Electronic computers)1 aIsaac, David.