Parallel Systems in the Data Warehouse

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. 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). 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.