Louisville SQL Server and Power BI User Group

Welcome

Welcome!

Welcome to the Louisville SQL Server Users Group! We represent the SQL Server community in Louisville, the surrounding metropolitan area, and throughout most of Kentucky. As a technical users group, we focus on monthly meetings, but also provide networking, learning opportunities, speaking opportunities, training, and collaboration for SQL Server professionals throughout the Ohio Valley area. Our monthly meetings occur on the second Thursday of each month, either at lunchtime in the downtown Louisville area or in the evening outside downtown. This alternating approach to meeting times and locations allows us to support as many of our users as possible and provides different venue and time options for our meetings and our attendees. We also partner with various volunteer groups to bring special events to the area, such as SQL Saturdays. Those events typically draw large crowds of SQL Server professionals from Kentucky, Ohio, Indiana, Tennessee, and beyond!

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Next Meeting

Thursday,

June

08

Columnstore Index Performance Gains

Description:  

In this session, James will demonstrate how columnstore indexes can be used to increase performance in data warehouse data loads and queries. We’ll cover the difference between clustered and non-clustered columnstore indexes. We’ll also cover the performance gains of columnstore data compression and best practices.

Speaker: James Chappell

James Chappell is a currently a Business Intelligence Developer at Republic Bank. He has 7 years of experience working the full Microsoft BI Stack as a BI Developer. He also has experience in designing and implementing BI continuous integration, Agile and ETL frameworks.

Featured Presentation:

Columnstore Index Performance Gains

James Chappell, BI Developer Republic Bank

In this session, James will demonstrate how columnstore indexes can be used to increase performance in data warehouse data loads and queries. We’ll cover the difference between clustered and non-clustered columnstore indexes. We’ll also cover the performance gains of columnstore data compression and best practices.

About James:
Will finish later

 

 

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