More On The “Achilles Heel Of Cloud Computing – Data Integration”

In March of last year I posted a blog here entitled: The Achilles Heel Of Cloud Computing – Data Integration.  “In fact, what currently limits the number of cloud deployments is the lack of a clear understanding of data integration in the context of cloud computing. This is a rather easy problem to solve, but it’s often an afterthought.”

So more than a year later, where are we?

While some progress has been made, many cloud computing implementation projects continue to ignore the value of a sound data integration strategy and the use of the right data integration technology.  Most paint themselves into a data quality and data synchronization corner, but give them time.

There is the whole “pay me now, or pay me later” kind of thing going on here.  You can either work a data integration strategy as part of your cloud computing deployment, which means it’s there the first day of operations.  Or, you can attempt to retrofit a solution and strategy after you’ve gone live.  I’ve worked both.  Clearly the best approach is to take some time to create a data integration strategy, and select technology beforehand.  Otherwise it’s like changing the tires on a truck while it’s rolling down the street.

So, here is where we are.  As businesses continue to deploy cloud-based systems, many ignore the fact that there needs to be some mechanism to synchronize data to and from your cloud and the core enterprise systems. By not addressing this now, you’ll have a data integrality and/or master data management issue in short order — an issue that will kill the value of your new cloud-based system before you receive the first invoice from your cloud provider.

Indeed, in many of the cloud projects that I see, data integration is an afterthought — or more often, not a thought at all.  While it’s not sexy like cloud computing, a data-integration strategy needs to be in the foundation of your cloud computing plan.  This includes cloud-to-enterprise and cloud-to-cloud.  The integration needs to be innate to the architecture; it can’t be something you’re reminded about at the rollout meeting.

So, what should you be considering?

First, someone needs to be responsible for data integration strategy and activities, and be allowed to contribute to all new and existing IT projects, particularly cloud computing projects.

Second, create a lab and begin evaluating, testing, and playing with data integration technology that works with cloud-based systems, both on-premise and delivered as-a-services.  It’s cheaper than you may think, and typically pays for itself with the first few projects.

Finally, create a master plan and architecture that provides a roadmap into the future.  This is required both for understanding, as well as budget and resource planning.




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