Cloud 2012 Redux

You shouldn’t have to commit everything at once

This year will be remembered as the year the cloud moved beyond the realm of “Back to Time-Sharing” or a curio for greenfields and start-ups.  While Software as a Service (SaaS) is interesting, it can not be a center piece of your IT infrastructure or strategy due to its limited scope and cost/scalability metrics.  By the same token, every IT system is not a greenfield opportunity, and most require a steady evolutionary response incorporating the existing infrastructure’s DNA and standards.

Just illustrating a “private cloud” with a “public cloud” next to it does not cut it.  What does that really mean?  Ever wonder what is really in that cloud(s)?  Better yet, in safe understandable steps, explain it; cost benefit 3-5-7 year projections, organizational impact for IT and business process, procedural impact for disaster recovery, etc.  Sorry, “Just buy my product because it is what I have to sell!” does not work; I need a tested time-phased architectural plan, with contingencies, before I commit my company and job.

For the first time in the continuing cloud saga, we have been able to put together and test a “non-aligned” approach, which allows an organization to keep IT infrastructural best practice and not “sign-in-blood” to any individual vendor’s ecosystem.  With the proper design, virtual machines (VMs), can be run on multiple vendors’ platforms (Microsoft®, Amazon.com®, etc.) and on-premise, optimized to cost, performance, and security. This effectively puts control of cost and performance in the hands of the CIO and the consuming company.

In addition, credible capabilities exist in the cloud to handle disaster recovery and business continuity, regardless of whether the supporting VMs are provisioned on premise or in the cloud. Certain discreet capabilities, like email and Microsoft Office™ Automation, can be “outsourced” to the cloud and integration to consuming application systems can be maintained in the same manner many organizations have historically outsourced functions like payroll.

The greatest benefit of cloud 2012 is the ability to phase it in over time as existing servers are fully amortised and software licences roll-off and require renewal.  Now we can start to put our plans together and start to take advantage of the coming margin-cutting wars of the Cloud Titans in 2013 and beyond.

Are you Paralyzed by a Hoard of Big Data?

Lured by the promise of big data benefits, many organizations are leveraging cheap storage to hoard vast amounts of structured and unstructured data. Without a clear framework for big data governance and use, businesses run the risk of becoming paralyzed under an unorganized jumble of data, much of which has become stale and past its expiration date. Stale data is toxic to your business - it could lead you into taking the wrong action based on data that is no longer relevant.

You know there’s valuable stuff in there, but the thought of wading through all THAT to find it stops you dead in your tracks.  There goes your goal of business process improvement, which according to a recent Informatica survey, most businesses cite as their number one Big Data Initiative goal.

Just as the individual hoarder often requires a professional organizer to help them pare the hoard and institute acquisition and retention rules for preventing hoard-induced paralysis in the future, organizations should seek outside help when they find themselves unable to turn their data hoard into actionable information.

An effective big data strategy needs to include the following components:

1. An appropriate toolset for analyzing big data and making it actionable by the right people. Avoid building an ivory tower big data bureaucracy, and remember, insight has to turn into action.
2. A clear and flexible framework, such as social master data management, for integrating big data with enterprise applications, one that can quickly leverage new sources of information about your customers and your market.
3. Information lifecycle management rules and practices, so that insight and action will be taken based on relevant, as opposed to stale  information.
4. Consideration of how the enterprise application portfolio might need to be refined to maximize the availability and relevance of big data. In today’s world, that will involve grappling with the flow of information between cloud and internally hosted applications as well.
5. Comprehensive data security framework that defines who is entitled to use the data, change the data and delete the data, as well as encryption requirements as well as any required upgrades in network security.

Get the picture? Your big data strategy isn’t just a data strategy. It has to be a comprehensive technology-process-people strategy.

All of these elements, should of course, be considered when building your big data business case, and estimating return on investment.