Brian Cox
Apr 30 2010
The terms data and information are often used interchangeably. However, in the data warehousing world they are quite different from each other. Remembering the difference is as simple as the difference between Charlie and Raymond Babbitt. You may remember these two characters from the movie Rainman. Charlie is the younger brother of austitic savant Raymond.
Mar 04 2010
Why use the native Unpivot transformation?
In my last post, I covered how to use an unpivot transformation in SSIS. There are, however, at least two other ways the same output can be achieved. In addition to the built in transformation, a multicast into a union all or a script task can be used. While all three methods produce the same dataset, the latter two are slower and one is much less efficient than the native transformation. If you are interested in each of the three methods, continue reading; otherwise, you can jump to the results.
Jan 26 2010
Unpivot in SQL Server Integration Services (SSIS)
When importing data from a flat file into a database it is not uncommon to be presented with a source that has repeating data sets. This data isn't normalized and usually needs to be split into a single row for each repeating group. Moving multiple matching sets of columns into rows can easily be done using the Unpivot transformation in SQL Server Integration Services (SSIS). For example, the following data is presented containing 2 columns that apply to every field (Date and Type), followed by 5 groups of 3 columns (Salesperson, Sales and Units).