5 Crucial Considerations for Big Data Adoption [INFOGRAPHIC]

jonathanbuckley
Posted by jonathanbuckley September 14, 2015
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Big Data is quickly going mainstream, but much of the buzz has focused on the various engines from Apache Hadoop to Apache Spark with less focus on the key business considerations that must be taken into account. The many use cases for big data make it easy to be taken in by all of the hype, but organizations run a huge risk if big data projects are unsuccessful or even never reach full production.

Big Data is quickly going mainstream, but much of the buzz has focused on the various engines from Apache Hadoop to Apache Spark with less focus on the key business considerations that must be taken into account. The many use cases for big data make it easy to be taken in by all of the hype, but organizations run a huge risk if big data projects are unsuccessful or even never reach full production. Currently only 13 percent of organizations acheive full-scale production for their in-house big data implementations, and only 27 percent of executives described their initiatives as successful.

Such low levels of success, should be telling for those organizations considering adopting big data to improve or run their business. The Hadoop ecosystem is complex, and failing to take that complexity into account when considering long-term performance can slow a project down tremendously. The infographic below identifies 5 key considerations when selecting either an on-premise or cloud-service vendor for a big data deployment.

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jonathanbuckley
jonathanbuckley
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In 2008, we formed The Artesian Network, LLC, a consortium of nine core marketing and sales professionals focused on finding and proving the repeatable, predictable revenue models for new companies in B2B technology. Though we are a senior team with very high technical adaptability, in recent years we have had demonstrated particular focus in data and network security, very large scale data management and analytics, artificial intelligence and the convergence with robotics and cloud infrastructure development. We are known for providing insights that are uniquely and strategically valuable, even if uncomfortable at times. Since we are involved at the early stage of the company lifecycle, when pursuing the repeatable business model sometimes the data comes in conflict with the original business thesis. This is where having senior counsel becomes crucial.