Cloud BI: Going where the data lives

As more companies store data in the cloud, they're increasingly crunching the numbers there, too.

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Even though cloud-based business intelligence has been around for nearly a decade, a recent trend is driving renewed interest: Companies are generating and storing more data in the cloud.

"What I think will happen is people will move the analytics app closer to the data," says Joao Tapadinhas, a Gartner analyst. "As more data sources move to the cloud, it makes more sense to also adopt cloud BI solutions because that's where the data is. It's easier to connect to cloud data using a cloud solution."

Researchers at Gartner say that 2014 may be the tipping point for cloud BI. In each of the last four years, around 30% of respondents to a Gartner survey said they'd run their mission-critical BI in the cloud. This year, however, nearly half -- 45% -- said they would adopt cloud BI.

Historically, cloud BI products have been most appealing to smaller businesses, in part because those are less likely to have an IT department that can manage an on-premises product. However, analysts are starting to see larger companies adopting cloud BI, typically starting with individual groups or departments.

Shifting data analytics to the cloud doesn't come without its challenges, though. For example, it's unlikely that all corporate data will move to the cloud, particularly in larger enterprises. That means many businesses will have to map data from both cloud and on-premises sources to the BI software, whether that software itself is on-premises or in the cloud. Also, bandwidth constraints may slow down data transfers and can lead to increased costs, if a business must upgrade its connectivity to improve data transfer.

Nevertheless, some businesses have already adopted cloud BI services, analysts report anecdotally, though specific figures aren't available. Many companies that have made the move say that the benefits -- including fast time to market, no need to maintain on-premises software and simplicity of use -- outweigh any downsides.

Mixing up data sources

Take Millennial Media, which sells a mobile advertising platform. It needed to pull together data from disparate sources, both on site and in the cloud.

Around two and a half years ago, Bob Hammond, CTO for Millennial, began looking into BI as a way to marry data from Salesforce with transactional and financial information from in-house systems and then let decision makers at the company visualize it.

"No human I know of can . . . make business decisions based on data that hasn't been brought together into a single source," he says. The company needed BI, he says, because "we weren't able to take data from multiple systems and connect that data logically and view that data in a UI so that we could understand what was going on."

He also wanted to let more people in the organization, like data analysts, assemble reports, rather than limiting report-making to technologists who know how to code and interact with back-end databases. Plus, he needed a system that was flexible so the software would be easy to maintain and it would be easy to create new use cases.

Hammond eliminated on-premises BI software options in part because he didn't want to incur the costs associated with managing and maintaining it. Time to market was also important.

Millennial ended up choosing Good Data's cloud BI offering and had its initial project in place in about three months. Subsequent projects have taken closer to a month to get up and running, Hammond says.

Sending on-premises data to Good didn't turn out to be much of a problem for Millennial. Each day the company generates around 10TB of raw data but transfers only around 18MB of compressed data to Good. "We do all the transformation of raw data into only the specific data we want in our systems before we transfer it into the cloud," he says.

Not all businesses do such a great job of managing that data transfer, though. "What we tend to see is it's rather difficult to keep the amount of data moving between the database and the analytics tool small," says Gartner's Tapadinhas. In other words, keeping data transfers small is important in cloud BI to manage both costs and upload/download bandwidth issues.

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