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Webcasts on Data Warehousing and Business Intelligence
Presented by the Kimball Group on June 6, June 20, July 11 and July 20 |
Over the last two decades, the Kimball Group has pioneered a method for successfully defining and implementing an enterprise data warehouse / business intelligence system. The Kimball Group’s The Microsoft Data Warehouse Toolkit, specifically applies this method to the SQL Server 2005 platform.
Please join us at the upcoming webcasts as the experts from the Kimball Group demonstrate, step-by-step, how the SQL Server 2005 platform solves the tough issues faced in implementing Data Warehouses and Business Intelligence applications.
TechNet Webcast:
Microsoft Business Intelligence (BI) Using the Kimball Method (Level 200)
When: June 6, 2006
9:30 a.m. to 10:30 a.m. Pacific Daylight Time
Presenter: Warren Thornthwaite
Real success in business intelligence (BI) is defined by both short and long-term results. For the short term, you can win with top priority, data quality, appealing to broad interest and high value. Long-term success however, requires constant growth and expansion, as well as a solid, well-designed foundation. Join this webcast to learn how to build a strong, scalable Microsoft BI architecture. Learn about the basic Kimball Method, the data warehousing/BI Lifecycle, the three tracks of the development phase, and many more details and issues you would be hard-pressed to anticipate on your own.
http://msevents.microsoft.com/CUI/EventDetail.aspx?EventID=1032297084&Culture=en-US
TechNet Webcast:
Designing a Scalable Data Warehouse / Business Intelligence (DW/BI) System (Level 200)
When: June 20, 2006
9:30 a.m. to 10:30 a.m. Pacific Daylight Time
Presenter: Joy Mundy
When you are building a data warehouse / business intelligence (DW/BI) system, scale is likely to be a major concern. Either you have a large system now, or you hope to grow to have a large system; or you have a small system but a tight budget, and you want to do more with less. What does large scale even mean? Is it determined by data volume, the number of users, complexity, or something else? What are the most important factors to consider? Join this webcast to learn techniques for addressing these and many other DW/BI issues. The session introduces and explains the Kimball Method lifecycle, and shows how to apply it to a scalable DW/BI system.
http://msevents.microsoft.com/CUI/EventDetail.aspx?EventID=1032297070&Culture=en-US
MSDN Architecture Webcast:
Using SQL Server 2005 Integration Services to Populate a Kimball Method Data Warehouse (Level 200)
When: July 11, 2006
11:00 a.m. to 12:00 p.m. Pacific Daylight Time
Presenter: Joy Mundy
How do you combine the tasks and transforms offered by Microsoft SQL Server 2005 Integration Services (SSIS) into a real extraction, transformation, and loading (ETL) system? In this webcast, we present design patterns for building an application that is maintainable, auditable, and scalable to populate your dimensional Kimball Method data warehouse and Microsoft SQL Server 2005 Analysis Services database. Learn best practices for overall system design, for populating dimension and fact tables, and for populating the audit dimension.
http://msevents.microsoft.com/cui/WebCastEventDetails.aspx?EventID=1032297072&EventCategory=4&culture=en-US&CountryCode=US
TechNet Webcast:
Getting Started with Data Mining (Level 200)
When: July 17, 2006
11:30 a.m. to 12:30 p.m. Pacific Daylight Time
Presenter: Warren Thornthwaite
Join this webcast for a comprehensive overview of data mining from a database development perspective. We begin with a discussion of the business value and uses of data mining, such as prediction and forecasting. Learn how to detect anomalies, and how to recognize scenarios for which Microsoft data mining technology is best suited. Using a typical business-driven approach to data mining, we show how to identify data mining opportunities, and cover the practical elements needed to make it work well, such as data preparation, model building, and validation. We then examine the output, consider different implementation methods, and conclude with recommendations on how to maintain your data mining solution.
http://msevents.microsoft.com/CUI/EventDetail.aspx?EventID=1032297086&Culture=en-US