Best Practices For Big Data

Is Cloud Computing the Best Way to Do Big Data Analytics?

On the surface, big data analytics and cloud computing have very little in common. After all, they are two entirely different animals living on totally opposite ends of the IT spectrum. Peek beneath the veil, however, and you’ll see that one looks as if it may have been specially made for the other.

Inside the Cloud

Cloud computing streamlines access to computing resources by incorporating unrivaled convenience into the delivery process. Storage, applications, services, servers, and even entire networks can be quickly deployed into live business environments with very little effort from the client or vendor. By leveraging service models such as Software-as-a-Service, companies can enjoy on-demand access to the resources they need via a pricing model that offers significant cost savings. Now take everything you know about cloud computing and swap big data as your resource. You see it. Massive potential.

Amazon, Google, Microsoft, and others are playing an active role in delivering big data analtyics from the cloud. While this trend is still relatively new, the benefits are already crystal clear.

Cost effective access. Cloud computing makes big data easily accessible to organizations on a budget. Upfront capital obligations are eliminated right off the bat, and operational expenses are often rolled into the per-usage costs.

Big data features. Cloud-based analytics platforms offer all the fixings. From real-time reporting to data visualization tools, you can find any feature you need to manage your data infrastructure.

Easy storage and scale. One of the biggest advantages of the cloud is its scalability. Whether you’re a doctor’s office who needs space for years of patient records, or a media company who needs to house scores of photos and videos, the cloud can provide storage on-demand at near limitless capacity.

Big Data Challenges in the Cloud

Big data and cloud computing make an ideal pairing, but there are some potential drawbacks to consider. Aside from all the known disadvantages of the cloud, businesses have to deal with the challenge of actually moving their data. Remember, we’re not talking about of files that weigh out to a couple hundred megabytes. In many cases, it’s multiple terabytes of information that need to be transferred. So in addition to topflight security and a comfortable level of control, companies have to emphasize finding a solution that can handle the vast amount of data they need to send to the cloud.

With such a massive volume of data to account for, big data projects are typically built around on scale and capacity, which is specifically why platforms such as Hadoop and NoSQL are used. From that perspective, the cloud is the perfect deployment model. Cloud computing provides the resources needed to ensure that heavy workloads flow smoothly from upload to reporting. Whether it’s deployed in a public, private, or hybrid form, rolling out a big data analytics platform over the cloud is definitely worthy of consideration.

What are your thoughts on the cloud in this scenario? Is it truly the best option for big data deployments?




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