SQLCAT: Designing Databases and Tuning Queries for Parallel Data Warehouse (PDW)
A variety of customers have been working with the new Parallel Data Warehouse -- PDW -- both in the TAP program and lab-based validation engagements. In this session we will share a number of best practices and learnings about optimal database design for PDW, pointing out any differences from SMP-based SQL Server, and walk through some real world examples of tuning complex queries to optimize performance.
Principal Group Program Manager
Stuart Ozer manages the Data Warehouse and BI group within the SQL Server Customer Advisory Team (SQLCAT). His team contributes to the architecture and deployment of the highest-scale applications built on SQL Server by customers worldwide. In addition to presenting best practices for these workloads through papers and conferences, Stuart’s team works to prioritize future product investments and improvements addressing the DW/BI market. Stuart’s latest efforts have been to drive early customer engagements with the new, scaled-out Parallel Data Warehouse (PDW) offering from Microsoft launching this fall. Stuart has been at Microsoft for 12 years. He recently returned to the SQL Product Group following 2 years inside Microsoft Research working for Jim Gray, where he collaborated with biologists in inventing a series of database-centric techniques for use in biomolecular sequence analysis. Prior to his work at Microsoft, Stuart co-founded and managed Infodynamics -- a San Francisco Bay Area data warehouse consulting firm focusing on enterprise-scale data integration and decision support solutions. His 25 years of industry experience include earlier product group and field consulting positions at Compaq, IBM and Metaphor.
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