Bringing enterprise analytics to the cloud

We’re coming to the tipping point for public cloud adoption, and it’s going to have big consequences for data warehousing, BI, and analytics. It’s no longer a question of if we’ll move analytics to the cloud, but rather of when.  There’s also a big question of what enterprise class data integration will look like in a hybrid cloud.

In terms of the Innovation Curve, we’ve moved from “early adopters” to the “early majority.”  According to a recent Gartner survey, this year saw a 50 percent jump in the portion of respondents who said they plan to run mission critical applications on the cloud, from about 30 percent in each of the previous four years to 45 percent this year.  Many companies – even Fortune 1000 – are mandating that all new infrastructure will be in the cloud.

Cloud benefits

Here’s a quick recap of cloud benefits. First, speed to market of solutions: cloud infrastructure can be provisioned in days rather than months and provides unlimited scalability to speed up jobs or handle volume increases. Gone are the multi-month projects that involve adding servers, disks, cages, racks, cores, routers, switches, cables, etc.  Also gone are the time and hassle of adopting new best-of-breed infrastructure technology. Second; renting can cost a lot less owning: with public cloud solutions you pay only for the resources you need when you need them. Price wars between cloud service partners (CSPs) are bringing down prices, and competition for enterprise business combined with economies of scale will continue for years. Third; data and analytics innovators are targeting products for cloud. Lastly, CSPs provide uniform coverage globally and across time zones. The most common objection to cloud adoption is data security, but the evolving conventional wisdom is that cloud data is already safer than many, if not most, data centers.

Starter projects for enterprise analytics in the cloud

CSP analytics tool stack is reasonably complete and growing. In fact, major CSPs support big data tools Hadoop and Map Reduce, SQL database management systems, and a variety of data visualization and dashboarding tools. Additionally, cloud solution partners are creating new methods to long time problems such as parallelizing statistical processing and automating common data integration tasks (e.g., adapters for SAP).

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