Why does big data need an opensource cloud server?

Now it does not make sense to buy a cluster of physical servers, since AWS or Azure can order the same capacity as virtual dedicated servers. By resorting to the help of the opensource cloud server, you are spared the need to purchase hardware, further configure it and connect to the network. In other words, you can immediately begin to use analytical programs, instead of spending a lot of time on deploying a physical infrastructure, choosing analytical programs for local use, and other related issues.

Lack of skills

Working with big data requires qualification. As you know, the market is experiencing a shortage of specialists in this field. Cloud solutions providers are constantly working to simplify big data analytics tools, providing more automation. They have the ability to quickly connect / disconnect as well as scale massive computing clusters, which reduces the need for specialists who have deep knowledge in the field of data analytics and are not so easy to find.

Risk reduction

Choosing a cloud to implement their big data strategies, the company thereby significantly reduces the risks. For example, when you start analyzing data, you don’t always know in advance whether they contain nuggets of valuable information. In the case of cloud solutions, you can upload a specific data set to a virtual cluster, analyze it and then collapse without serious consequences if the analysis did not bring the expected result and all this without any risks for the project.

Additional costs vs large initial investment

Each risk level corresponds to a certain level of financial costs. The cloud deployment model, including those associated with big data, provides for a payment plan when the consumer only pays for the services he uses. In practice, this means that if your pilot project does not give a return, you can close it by recording financial losses in a timely manner. They may turn out to be orders of magnitude higher if expensive equipment was purchased for the implementation of a project that was closed for some reason.

Elasticity

Cloud flexibility gives greater transparency to the project implementation process. When you begin to build a physical cluster of servers, you are limited by their performance level, which depends on the amount of memory, processor power, bus bandwidth, and storage. For comparison, if a cluster of 100 nodes is required to process an array of data for 10 hours to solve an analytical problem, then for the same price in the cloud, you can use 1000 nodes, having completed the work in an hour.