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PASS 2003 Review Conference Highlights • Keynote speakers • Gordon Mangione • Alan Griver • Bill Baker • Technical sessions • Over 120 sessions across 4 tracks • Dev team, MVP’s, SQL Server experts • Other benefits • • • • Pre-conference seminars Ask the Expert sessions Hands-on labs (RS and Yukon) Solutions Expo Chapter News • PASS membership benefits • • • • Education opportunities Networking value Discounts on SQL Server-related tools On-line access to information • More support for local chapters • • • • Regional seminars and road shows Give-aways (software, books, etc.) Administrative assistance Recorded content from Pacific NW group PASS 2004 • • • • Start planning now! Sep 28 – Oct 1 Orlando, FL Save on registration • PASS membership • Early-bird registration • Group discounts Yukon Preview Improvements Everywhere • For the DBA • • • • Disaster recovery improvements Data partitioning Improved replication Management tools • For the developer • • • • • • .NET CLR integration XML technologies T-SQL enhancements SQL Server Broker Notification Services Development tools Improvements Everywhere • For the BI/DW developer • • • • • • Rewritten DTS Rewritten Analysis Services Improved data mining Reporting Services Scalability and performance Development and management tools • Its been said… • More work on Yukon than all prior versions • Major investment in DTS and AS teams • Ready to handle 10+ TB databases DTS Preview • Complete redesign and rewrite • New development paradigm • • • • Develop packages in BI Workbench (VS.NET) Debug packages (interactively!) Deploy packages to Yukon server Configuration files set package properties • New DTS Designer paradigm • Control flow (tasks, constraints, containers) • Data flow (sources, destinations, tasks) • Event tasks Control Flow • Tasks • • • • All your old favorite tasks plus… File System Task AS Execute DDL Task Data Mining Query task • Precedence constraints • Mainly the same as before • Supports logical “OR”ing as well as “AND”ing • Containers • Sequence container • For Loop container • For Each Loop container Data Flow • Sources and destinations • OLE DB, flat file, raw file, recordset • Tasks • • • • • • • Aggregate, character map, conditional split Copy/map, data conversion, data mining (3) Derived column, fuzzy grouping, fuzzy lookup Lookup, merge, merge join, multicast Pivot, sort, union all, unpivot Dimension/partition processing Slowly changing dimension • Truly enterprise class features! DTS Demo Analysis Services Preview • Complete redesign and rewrite • Introduces Unified Dimension Model • Blurs the line between relational and OLAP • Basis for an AS database • Traditional benefits of OLAP • Query speeds, analytical richness, ease of use • Traditional benefits of relational • Complex schemas • Support for wide set of attributes • Low latency data • Will drive “sea change” in BI design • Features designed around UDM Data Sources and Views • Data sources • Provide connections to databases • One AS database (UDM) can include many • Data source views • Create logical model across data sources • Can include additional meta-data • Logical views based on single or multiple tables • Additional columns based on calculations • Logical names for physical tables and columns • All else based on DSV Dimensions • Attribute based • • • • Dimension can include MANY attributes Each can become a “hierarchy” Other hierarchies built based on attributes Provides rich query and filter options • Types and properties • Still support star, snowflake, parent-child • Still support member properties • Many more options for dim and level types • Translations • Can include for dim, hierarchies, attributes • Based on underlying columns in DSV Cube • One cube per database!! • Can include multiple fact tables • Measures put into measure groups • Measure groups related to dimensions • Support for inferred and many-many relations • Calculations based on MDX script • Evaluated in procedural order • Basically the same properties as today • But, cool new wizards to add common ones! • Actions • Same basic paradigm as today Cubes • Partitions • Same basic paradigm as today • Includes new “proactive caching” feature • Perspectives • Create “views” of the cube for analysis • Somewhat like virtual cubes today • Based on measure, dims, and calculations • Translations • Ability to provide translations much like dims • Based on underlying columns in DSV Cubes • KPI’s • • • • New feature to analyze trends Based on measure or calculated member Provides visualization on change and trend Will require new/updated front-end tools • True enterprise-class BI features! AS Demo