Business Intelligence Blog from arcplan

The Practicalities of Moving BI Into the Cloud: Part II


In Part I, I talked about a couple of reasons why cloud BI hasn’t gone mainstream yet – the inherent complexity of BI systems and the amount of data produced daily. Then I presented a secure way for data to remain in place but your BI to move into the cloud. (web services-based SOA broadcast services, essentially querying data that exists behind your corporate firewall from the cloud). Today let’s weigh the risks vs. rewards of moving your BI to the cloud.

Choosing a Cloud BI Vendor
Do you stick with your familiar BI software as it adapts to a SaaS model or go with a newcomer offering true SaaS? Be sure to carefully consider your business requirements and go with a vendor that meets them. You may risk going with a smaller vendor, but you are more likely to get the BI deployment you want.

Certainly evaluate the long-term cost of ownership – cloud BI may be more affordable at the outset and allow you to avoid the capital expenditure approval process, but will it cost more in the end? The reward of a quick implementation and “easy out” may be worth the risk of higher long-term cost and may lead to additional benefits, like allowing you to scale your BI to more users throughout the organization faster.

Time Savings
Sticking with an in-house BI deployment results in your IT team spending time to set up, tweak, maintain, and debug servers – time that could be better spent elsewhere…

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The Practicalities of Moving BI Into the Cloud: Part I


Many (if not most) companies are evaluating the benefits and risks of cloud-based solutions this year. In fact, marketing research firm IDC predicts that businesses will spend $22.6 billion on cloud services by 2015. However, there is one area that has fallen behind the cloud – business intelligence. But it’s ready to emerge. Even organizations with traditional (hosted on-premise) BI systems in place can make the move. Let’s consider the practicalities of doing so.

Organizations that have deployed business intelligence have first-hand knowledge of the complexities of such a system – the vast network of linked parts and pieces, from data warehouses to ETL applications, OLAP servers to analytical dashboards. It’s a jungle out there and it’s clear that it can’t continue this way for much longer. A more repeatable and sustainable model for business intelligence must emerge – one that reduces the complexity while maintaining security and enhancing ease of use.

The Data Question
For services like CRM and document collaboration, the roadmap for moving to the cloud has already been established by companies like and Google. But for BI, it’s not as clear. The sensitivity and volume of data as well as the inherent complexity of BI systems have left executing a cloud-based BI strategy more of a dream than a reality.

Many believe that the next logical step in BI’s evolution is moving it to the cloud. However, when looking at the characteristics of a modern day BI deployment, it’s easy see how getting there is complicated.

Let’s take a look at just one aspect of a cloud BI deployment: the amount of data that would need to be moved, stored, and processed. There’s a reason we’re all talking about big data these days – according to April Adams, research director at Gartner, data capacity in enterprises is growing at 40% to 60% year over year…

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