Cloud deployment and Big Data, the flashiest BI & Data Warehousing concepts from 2013, have carried forward into 2014 with continuing momentum. Companies just beginning to understand the value proposition for Big Data solutions for their enterprises are taking their prototypes and proofs-of-concept out of the lab and now must decide where to put them when they are ready to “productionise” and turn the system over to the users. BI Architects are asking themselves, “Do I put it in the data centre like a traditional enterprise application deployment or in the cloud?”
In this week’s article, we’ll talk about the advantages of a cloud deployment for your BI solution. Next time, we’ll talk about the advantages of an in-house or traditional deployment.
Cloud BI Advantages
Some of the biggest challenges for BI deployments are anticipating and responding to changes in data volume and consumption patterns. As we learned when we first started deploying BI solutions over a decade ago, our customers eventually outstrip even the most aggressive deployment architectures with increasingly demanding interactive and batch processing expectations. So what’s the lesson? We must anticipate that the architecture will be inadequate for future demand and bake the flexibility of the solution into the architecture from the outset. In a cloud-deployment scenario, that flexibility is simply accomplished: adding bandwidth, disk volume, and processing power is often as simple as a few mouse-clicks, or at most a call to the vendor (and of course, a check!). Cloud solutions provide superior flexibility and configurability. This flexibility even extends to day-by-day utilisation optimisation, as processing power or bandwidth can be grown or pruned to meet seasonal or even hourly changes in the demand pattern of a company’s consumption. This can avoid the costly scenario of buying capacity or processing power in a data centre to meet the (occasional) peak demand, while the servers otherwise sit underutilised.
Another benefit of cloud deployment is the simplicity of deployment. By pushing the burden of infrastructure ownership and maintenance to a service provider, companies can focus their attention on ensuring that the Big Data solution is focused on including and processing the right data. Moreover, service delivery contracts can be negotiated in such a way that the vendor is a partner with the customer in the success of the platform. For example, by negotiating that lapses in service leave the customer with some kind of financial recompense, the vendor is incentivised just as the company’s own IT organisation would be if the deployment were done internally.
The vendor-partner has “skin in the game” for the deployment’s infrastructure stability, responsiveness, and effectiveness. For companies who want to put their solution in the cloud, demanding that the vendor shares in the ownership of the platform’s service delivery is key to ensuring that the company does not find itself shackled to a deployment only part of which they can control, should service delivery start to dip into unacceptable levels.
In the next article, we’ll talk more about the advantages of keeping a Big Data project in-house via a traditional data centre deployment. Come back soon to hear more about this!
DataHub Writer: Douglas R. Briggs
Mr. Briggs has been active in the fields of Data Warehousing and Business Intelligence for the entirety of his 17-year career. He was responsible for the early adoption and promulgation of BI at one of the world’s largest consumer product companies and developed their initial BI competency center. He has consulted with numerous other companies about effective BI practices. He holds a Master of Science degree in Computer Science from the University of Illinois at Urbana-Champaign and a Bachelor of Arts degree from Williams College (Mass)..
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