Another major enhancement, called Tablix, is a new data element type that combines table, matrix, and list. Tablix gives you an easy way to work with grouping by allowing you to group on columns or rows as well as define adjacent or parent/child groups. All of this sounds fairly intuitive, but it does take a little training. I quickly found that building groups the way I did in the previous version left me out in the cold. I had to slightly change the way I authored reports to be successful.
Report Builder has come a long way as well. Microsoft has removed a number of limitations that could make it difficult to work with. Now, you can do almost anything in Report Builder that you can do in Visual Studio, and Report Builder comes with wizards that make formatting data and charts automatic. I have almost no reason to write reports in Visual Studio anymore. This new version of Report Builder (2.0) wasn't available when Katmai shipped, but it is available as a separate download now.
SQL Server Integration Services
Microsoft has taken some big steps to ensure that SSIS (SQL Server Integration Services) can compete directly with competitors such as Informatica by offering lookup caching and CDC. And while CDC isn't strictly an SSIS enhancement, SSIS does take advantage of it to increase the speed of ETL processes. In fact, both lookup caching and CDC can improve the speed of loads by orders of magnitude. Let's examine a couple situations where you'll see dramatic performance gains.
Perhaps you're loading customer data, and you have to load each customer one at a time because you have to look up other information and make load decisions based on that lookup data. In SQL Server 2005, you would put this load inside a "for each" loop container and perform the lookup on each customer as you iterate through the loop. This means that you would perform the lookup itself for every customer. Well, if you have a large lookup table -- say, something in the neighborhood of 500 million rows -- you would have to query that data for every row you import. And if the lookup table is not on the same system or if it's not indexed appropriately for your lookup, those lookups could take a lot of time.
Now, in SQL Server 2008, you can perform that lookup once for all the customers and cache the data in a local file. The upshot is that iterating through the loop will go much faster.
Another scenario where SSIS improvements come into play is in handling changed data. Let's say a customer address change needs to be reflected in the database you're loading. In SQL Server 2005, you have to perform a binary or text comparison, on a row-by-row basis, for each column you want to track. This means that the larger your customer table, the longer your lookup will be. But with CDC, you can easily see which rows and columns have changed and avoid the lookup altogether. Here again, you could reduce the time to load tremendously.
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