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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
• 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
• 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
• 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
• 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