• Feedback on MSDE 1.0 (SQL 7) was lack of documentation. Where to get it. The limitations. How to connect to an existing MSDE instance if it’s there and the password has been changed? Servicepacks taking too long to install. Licensing not clear.
• Will now ship on CD with all Editions of SQL 2000. Freely distributable with purchase of any SQL 2000 edition. Need a CAL to talk to SQL Server standard/Enterprise edition.
• Can act as a merge replication subscriber and publisher. Transactional subscriber only. Snapshot subscriber and publisher.
• 2GB ram max, 5 concurrent workload throttle, 2GB database size (data files only – no limit on transaction log). Supports up to 2 cpu’s. No FTS. No OLAP. No tools.
• Workload throttle means 5 concurrent queries are allowed. Any more and the engine throttles back. Throttling affects all connections.
• Runs on Windows 2000 (all), NT 4.0 (all), Win98. IE5 required for DTS FTP custom tasks. (Win95 support dropped).
• Min 32MB ram for Win98. Min 64MB for NT4/Windows 2000.
• Re-distributable – 24MB in size. Installs to 38MB (core) with no replication, agent, dmo, dts. 48MB with all these.
• P166 for Win98. P200 for NT4/W2K.
• Upgradeable to all other SQL Server editions.
• Now had multi-instance support
• Windows Installer based setup.
• Can now detect when throttling has occurred. Dbcc concurrencyviolation shows a histogram of violations – shows how many times and by how much the limit has been violated. Entries also written automatically to the errorlog.

Trevor Dwyer’s Notes

Data Mining Enhancements

The data mining features of Analysis Services are incorporated in an open and extensible implementation of the new OLE DB for Data Mining specification. Data mining algorithms developed by Microsoft's Research department are provided that you can use to discover information in your databases and OLAP cubes.

Relational and OLAP Data Mining

Analysis Services has incorporated data mining technology so that you can use it to discover information in relational databases and in multidimensional cubes. You can use the results of data mining to create a dimension that you can add to a cube to further analyze your data. For more information, see Relational versus OLAP.

Microsoft Decision Trees

The Microsoft Decision Trees algorithm uses classification techniques to analyze data. It then constructs a decision tree that can be used to predict probable values for similar data. For example, you could use this algorithm to analyze credit history data and predict the credit risk of new applicants. For more information, see Microsoft Decision Trees.

Microsoft Clustering

The Microsoft Clustering algorithm uses a nearest neighbor method to group records into clusters that similar characteristics. Often, these characteristics may be hidden or non-intuitive. A simple use of clustering would be to find age ranges in customer data. For more information, see Microsoft Clustering.

Third Party Algorithms

You can use data mining algorithms developed by third parties in accordance with the OLE DB for Data Mining specification. For more information, see Using Third Party Algorithms.

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