Okay, now this could be a completely nuh-uh topic. But in the real world these things can and do happen. Example: There is this cube developed a couple of years ago, deployed on various environments such as QA, UAT, Production etc. Then something goes wrong when some new dimension data has text that is longer than what the field allows – ETL fails. You figure it is a small change to the dimension table: field QuarterName on table DimDate needs to be varchar(15) instead of the varchar(9) that it is. So you go fix it directly on the database – Big mistake when it comes to ALM etc. However, the ETL works. But, when you process the dimension on SSAS you get an error:
Errors in the back-end database access module. The size specified for a binding was too small, resulting in one or more column values being truncated. Errors in the OLAP storage engine.
Continue reading Doing the Forbidden: Fixing Cubes and Dimensions on Production et al.
I had proposed using proactive caching for a near real-time cube, and the idea was that when the ETL was done every five minutes, proactive caching should automatically kick in to process the cube.
Seemed simple. Configuration was simple. And it worked as expected on development and QA environments. But on UAT, proactive caching would simply not start. Everything was configured just as it was on dev and QA. Permissions were also perfect, but for some reason proactive caching would simply not kick in to automatically process the cube once the underlying table was updated. The ETL runs every 5 minutes and takes only a minute to update the underlying table, so I knew exactly when silence interval should start telling the analysis services to start processing – yet nothing happened.
Continue reading Proactive Caching: Automatic Processing would not start
If you had flown AirAsia, you would probably know where I stole the title to this post from. Microsoft did the same thing too. Heh heh! No, not the stealing bit, but providing for (almost) every small organization to use BI – Something which only the big bucks could afford.
Continue reading Now Everyone Can BI