Analysis Services (Getting Dimensional with Data)(Optimising Analysis Services) and Excel (not a bad Data Mining client at all) with Chris Testa-O'Neill, Steve Wright and Allan Mitchell SQL Server MVP. Evening sponsored by SQL Sentry, Inc
The Event Limit (physical attendance) has been reached - we are now operating a reserved list - I will email on Tuesday with place confirmations; If you registered before this week you are fine. The sessions will be broadcast via LiveMeeting for those who don't get a phyiscal place.
Live Meeting URL: https://www.livemeeting.com/cc/mvp/join?id=FHSQ2S&role=attend
Meeting is sponsored by:
Finally a complete performance monitoring and optimisation solution for the entire Microsoft BI platform.
SQL Sentry are giving up a prize of a full licence for SQL Sentry Performance Advisor (a $1,495 value prize - no cash alternatives!); draw entry is via business card or leave your details at the meeting.
18:00 - 18:30 - Introduction, Networking and Food
18:30 - 19:30
Excel – not a bad DM client at all
Microsoft is making a push to make DM something that everyone can use. The Excel add-in is a huge leap towards making that a reality. In this session I will show you how we can design, train and query a variety of model types and also get good visualisation of the results.
19:30 - 20:00
Steve Wright, Director of Product Support, SQL Sentry, Inc.
Optimizing Analysis Services
We are proud that Steve will provide the first public demonstration of SQL Sentry Performance Advisor for Analysis Services will demonstrate an insightful, efficient and effective approach to the management and optimization of Analysis Services. This session is available as a live meeting as well.
20:00 - 20:15 – Break
20:15 - 21:00
Getting dimensional with data
To complement Allan's presentation, Chris will provide an overview of the steps required to create a cube in SQL Server Analysis Services. Exploring the use of Data Sources and data source views to define the source data that the cube will use. Understanding the importance of Dimensions and how hierarchies can be added to improve the user experience of browsing a dimensional data . To bringing the cube together with measures that will hold the business metrics that intersect each dimension in a cube.
off Portland Street,