I’ve presented at the PASS Summit several times over the past years, and I’ve really enjoyed it every time. The Summit is great event for learning from some of the best in the SQL Server community, and you get a chance to spend time with them at the various events going on at the Summit. This year, the community’s getting the opportunity to vote for their preferred sessions, which I think is a great way to get people involved in the selection process. The deadline is May 20th according to the webpage (though another page says the 30th – probably better to vote early than to miss the deadline).
This year, I’ve submitted several sessions.
Do More (ETL) with Less (Effort) – Automating SSIS
SSIS is a great tool for transferring data from one data source to another, and for implementing complex ETL processes. However, for simple, straightforward data transfer tasks or packages that adhere to a pattern, creating SSIS packages by hand can be time-consuming and repetitious. By attending this session, you’ll learn how to automate package creation in SSIS, including the dynamic generation of data flows. We’ll cover some of the free and open source tools available for this, and discuss “roll your own” options.
Do You Know the Data Flow?
The Data Flow task is one of the most powerful and most complex tools available in SSIS. Whether you are brand new to SSIS, or you’ve been using it for a while, it’s likely you’ve had some questions about the Data Flow. Why are some components so much slower than others? Why can’t I store a value (like a row count) in one component, and use it in another component later in the Data Flow? And why does it always seem to be the part of my package that fails when I run it against real data? Well, you’re not alone. During this session, we’ll answer these questions (and many others) by learning how the Data Flow operates internally. We’ll cover the Data Flow from the basic (what’s a component?) to the advanced (how can I determine how many threads my Data Flow is using?). After attending this session, you’ll know a lot more about getting the most out of Data Flows in SSIS.
Handling Advanced Data Warehouse Scenarios in SSIS
So you’ve used SSIS to populate a simple star schema data mart, and everybody’s happy. But now you have new requirements that require more advanced data warehouse approaches, like late arriving dimensions, bridge tables, parent child dimensions, and Type 3 or Type 6 slowly changing dimensions (SCD). How do you handle those in a scalable, efficient way in SSIS? This session will present some common patterns for handling these scenarios. You’ll learn when to use each advanced approach and the pros and cons associated with each pattern. You will learn how to implement these patterns in SSIS, and how to tune them for high performance.
Tuning Analysis Services Processing Performance
You’ve got your Analysis Services cube created, and deployed in production. However, you notice that every night, the cube is taking longer and longer to process, and users are starting to complain about their data not being ready when they arrive in the morning. If you’ve found yourself in this situation, or want to avoid being in it in the first place, come to this session. We’ll cover how to benchmark processing performance, track down bottlenecks, and how to tune things to get the best performance for processing your cube.
Other Sessions I’d Like to See At the Summit
This is not an exhaustive list, by any means – so if you aren’t on the list, please don’t take it personally. These are the ones that happened to catch my eye as I looked through the list. Some because they had an interesting technical focus, some because I know the speaker will bring an interesting perspective on the topic, and some because…, well, just because I can.
Dynamic Business Rules Processing Using SSIS – Tim Mitchell
Techniques for Automating T-SQL Unit Tests and User Acceptance Testing – Scott Currie
Advanced Analysis Services Development – David Darden
Advanced SSAS Security – Chris Webb
Analysis Services Power Tools – Darren Gosbell
DAX Deep Dive – Marco Russo, Alberto Ferrari
