Check my blog post on TechNet over Performance Monitoring with SQL Server 2008 here. Feel free to pass your comments.
Archive for January, 2008
BPA 2005 – Jan build January 26th, 2008
The January 2008 package contains:
- BPA UI and command line tools
- Rules (previous rules + ~60 new rules)
- Rich documentation
Windows Server 2008 Security Guide January 24th, 2008
When released in early 2008, the Windows Server 2008 Security Guide will provide IT professionals with best practices and automated tools to help strengthen the security of servers running Windows Server 2008. The guide is now in Beta release, and is available for your review on Microsoft® TechNet.
101 with SQL CE 3.5 January 23rd, 2008
With Microsoft SQL Server Compact 3.5 and Microsoft Visual Studio 2008, developers have an easy-to-deploy solution for local data. Ranging from caching reference data to full offline scenarios, developers can use a single engine for their Windows Mobile-powered devices, or their full desktop clients–benefiting from the power of SQL Server in a compact footprint. Using Visual Studio 2008, we show how SQL Server Compact can be transparently deployed with unique features including updatable result sets and a custom document format, and how to manage the creation and maintenance of your local data. This session is packed with demonstrations that can get you started today. Check the webcast page here to know the same !!!
Analysis Services Many-to-Many Dimensions: Query Performance Optimization Techniques January 21st, 2008
Many-to-many dimension relationships in SQL Server 2005 Analysis Services (SSAS) enable you to easily model complex source schemas and provide great analytical capabilities. This capability frequently comes with a substantial cost in query performance due to the runtime join required by Analysis Services to resolve many-to-many queries. This best practices white paper discusses three many-to-many query performance optimization techniques, including how to implement them, and the performance testing results for each technique. It demonstrates that optimizing many-to-many relationships by compressing the common relationships between the many-to-many dimension and the data measure group, and then defining aggregations on both the data measure group and the intermediate measure group yields the best query performance. The results show dramatic improvement in the performance of many-to-many queries as the reduction in size of the intermediate measure group increases. Test results indicate that the greater the amount of compression, the greater the performance benefits—and that these benefits persist as additional fact data is added to the main fact table (and into the data measure group). Read the whitepaper on the Best Pactices site and download the same for offline reading here.