I feel a little like Thomas Jefferson when I say, "We hold these truths to be self-evident, that all code has certain unalienable rights and that among these rights is the ability to be thoroughly unit tested in a simple and concise way so bugs can be easily identified and production outages minimized." A bit dramatic, yes, but it gets my point across. Of course, most developers believe their code should be unit tested, but what happens when the definition of "code" is blurred? This was the situation I found myself in recently when presented with a complicated issue and tasked to find a solution. A group of developers was involved with writing a complex online analytical processing (OLAP) cube using SQL Server Analysis Services (SSAS). This cube had numerous dimensions all tied to an extremely complex fact table. Because the developers were quite skilled at developing cubes, they were able to piece the cube together, but validating the results of their Multidimensional Expressions (MDX) queries was a daunting task. The difficulty was compounded by a number of factors, including the amount of data in the dimensions and fact table, as well as the time and computing resources needed to build the cube. Once the cube was built, the results (produced by MDX queries) were sent to the users. If the users found an issue with the data, it would take a long time to track the problem down. Also, once the underlying problem was discovered and fixed, the cube would need to be regenerated. To make matters worse, if dimensions were added, the underlying fact table was updated or the cube was built using different aggregations, there was no way to determine the full effects of these changes. A seemingly innocent change could have a far-reaching and cascading effect on queries to the cube.


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