Brian Cox

Sep 29 2011

When merging, watch your asterisk

Recently, while working with T-SQL's merge statement and its output clause I ran across an error I couldn't track down.  My statement looked something like this:

 

Merge #target_1 as target using 
(select value1 from #source ) as source 
on target.value1 = source.value1 
when not matched then insert (value1) values (value1) 
OUTPUT $action, inserted.* into #action_target;

The code was producing this error

Msg 213, Level 16, State 1, Line 25
Column name or number of supplied values does not match table definition.

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Mar 01 2011

LogiXML - Steps in the right direction, but still a ways to go

A few fellow CapTechers and I recently had the opportunity to attend on-site training for LogiXML's Business Intelligence tools. While the LogiXML Info and Ad Hoc tools seem fairly comprehensive, there is still room for improvement on the development end of things.

LogiXML's two BI tools are very similar.  While the Info is more geared toward technical power users, the less powerful Ad Hoc option is more business user friendly. This seems to be fairly standard among most companies’ BI offerings and LogiXML is toeing that line fairly effectively. That said, most of our training focused on LogiXML Info and that’s where the majority of this post will focus.

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Apr 30 2010

Data vs Information

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. 

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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. 

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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).

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