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Adding Cloud to Your Analytic Ecosystem

Adding Cloud to Your Analytic Ecosystem
It’s a common question: what should a business executive consider when determining the best approach for adding cloud to an analytic ecosystem?
We at Teradata have thought a lot about this topic because our customers have substantial environments with significant amounts of data, many dozens or hundreds of applications, and thousands of users all over the world.
Planning for such a “large” scenario in the cloud is vastly different than thinking about what would be required for a “small” or greenfield system because the needs of the latter are orders of magnitude less taxing than those of the former.
And to be clear, I’m not suggesting that tiny is any less important than big; what I’m saying is that the solutions used to address the “large” set of challenges are vastly different than the solutions used to address the “small” set of challenges. This is the case regardless of technology, too: stocking your refrigerator is quite different than stocking an entire grocery store. It’s the same with analytics in the cloud.
As the saying goes, “Quantity has a quality all its own” – and good luck to the executive who assumes that what works in a small analytic proof of concept (POC) will necessarily scale up to work in a large, mission-critical environment. Throughout our history we’ve seen companies leave and then boomerang back once they realize that the grass is NOT greener on the other side of the fence. Buyer beware.

Do This – Don’t Do That

Advice: when contemplating migration to the cloud, or when constructing a hybrid (combination of on-premises and cloud) architecture, one should never start with technology and see how it applies to their requirements.
The reverse is the best approach: start with business requirements and then evaluate which tradeoffs, architectures, tools, and mitigation plans are needed to meet the needs. Failing to start with business requirements often leads to an expensive, short-lived “project” rather than an effective, long-term solution. Don’t be “that guy” who assumes. Trust, but verify.
From a business requirements perspective, an ideal cloud analytic solution is one that:
  1. Blends seamlessly with existing (usually on-premises) infrastructure and applications
  2. Takes advantage of native cloud capabilities, including security and integration
  3. Avoids any sort of vendor lock-in which would constrain choice and flexibility in the future
Unfortunately, most folks tend to place too little thought on the first point, because while greenfield cloud deployments are extremely rare – especially for any organization which is not a startup – it is easiest and simplest to talk about a scenario in which there is nothing to bring along. But, having zero legacy systems or technical debt is probably not (your) reality, so blue sky thinking can only take one so far.

Pick Your Partner with Care

Some of the characteristics that go into what we advocate as a cloud solution include:
  • Consistent user experience regarding the tools, languages, and operating procedures with which your users are already familiar – thus speeding time-to-value and creating an all-encompassing ecosystem rather than separate silos of analytics.
  • Consistent enterprise-class security that lines up with existing corporate policies and role-based access controls – thereby making it easy to operate, govern, and audit across all systems as a cohesive entity. Again, the integrated whole is MUCH more valuable than an itemized sum of the parts.
  • Advanced optimizer and workload management which enables users and administrators to monitor and manage performance and cost – and adjust manually or automatically to yield the desired mix of outcomes (benefit) vs. inputs (cost).
Let’s cut to the chase: the best (and fastest) way to achieve the right cloud solution FOR YOU is to partner with experts who have “been there and done that”. As with any complex undertaking offering high return yet also high risk, starting with a trusted advisor is the soundest approach to a successful outcome.
As the saying goes, “Only a fool learns from his own mistakes. The wise man learns from the mistakes of others.”
Do yourself a favor: Be smart and choose your cloud partner wisely. We at Teradata are here to help.
Portrait of Brian Wood

Brian Wood

Brian Wood is director of cloud marketing at Teradata. He has over 15 years' experience leading all areas of technology marketing in cloud, wireless, IT, software, and data analytics. He earned an MS in Engineering Management from Stanford, a BS in Electrical Engineering from Cornell, and served as an F-14 Radar Intercept Officer in the US Navy.
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