Business intelligence in the cloud is a hot topic recently, as part of the hype surrounding the cloud in general. I am not a big fan of cloud BI and I have mentioned that several times. However the topic does merit discussion.
The advantages of the cloud over on-premises are pretty straight forward. However, as far as business intelligence implementations are concerned, the question to me was always whether the benefits outweigh the unique challenges the cloud introduces. If all business data was in the cloud, there was a definite case to make for implement business intelligence software in the cloud. But since most business data isn’t, the benefits of cloud BI are not as obvious.
The blogosphere and analyst community in the business intelligence space are not sparing any words on the subject. There are several startups in this space as well, such as GoodData, PivotLink and others. But is the business intelligence space really heading in the direction of the cloud? I believe the answer is no.
The main reason I do not believe that the BI space is headed towards the cloud (at least for now) is because business intelligence backbone technology doesn’t seem to be headed there. In fact, it seems to be going in the opposite direction.
If you take a careful look at the new technology promoted by the established business intelligence vendors like SAP, IBM and Microsoft, and even those promoted by slightly less established vendors (yet successful) such as QlikTech and Tableau – it is all technology that is either ‘desktop enabling’ technology or in-memory technology.
These technologies, in-memory in particular, aren’t very cloud friendly and weren’t designed with the cloud in mind at all. They are designed to extract more juice out of a single computer, but very hard to distribute across multiple machines as in the case in most cloud implementations. Also, to benefit significantly from these types of technologies, you need very powerful computers, a premise which goes against proper cloud architecture that dictates that computing operations should be parallelized across multiple cheaper machines.
On the other hand, the current cloud BI platform vendors are using the same traditional backbone technology the on-premises vendors do, and by that they suffer from the same drawbacks most BI vendors do such as complexity and long development cycles. And when these drawbacks come into play, whether the data is in the cloud or on-premises isn’t even the main issue.
Even if the ‘pure cloud’ BI platform vendors did develop better technology more suited for running BI in the cloud, it is still years away. So while you can use the cloud for some types of solutions (mainly around other cloud data sources) the fact of the matter is that the cloud BI hype is at least a few years too early.
By: Elad Israeli | The ElastiCube Chronicles - Business Intelligence Blog
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