Big Data on the cloud, and for good reasons: from aiding the discovery of new drugs to predicting weather forecasts, earthquakes. Big Data analytics and the cloud are proving to be a dominant combination. Today scenario Cloud computing is a business enabler having a potential to take the business to the next level.
For any business, data is the most bases, for any transformation in the business; therefore, managing proliferating data is crucial.
Most of the big data projects are processed in the public cloud. Big data is required to be scaled on distributed cluster as per the demand and requirements. The biggest factor to process big data is data gravity and data elasticity. Cloud has a big role to play to get this done.
There seems to be a dire need for the adoption of big data over cloud such that the business gets benefited with instant reporting and analytical requirements. The main reasons for efficiently managing structured, unstructured and semi-structured data of varying sizes over cloud are as follows:
Excellent bi-directional Scalability (Vertical & Horizontal)
As per the definition, Elasticity in Big Data analytics calls for innovative processing and volume requirements, in order to meet the 3V property of the big data, namely velocity, veracity and volume of the data, necessitates additional infrastructure. Additionally, the demand for processing power is not uniform, fluctuating at different times of the year. While traditional solutions would require the addition of more physical servers to the cluster in order to increase processing power and storage space, the virtual nature of the cloud allows for seemingly unlimited resources on demand. With the cloud, enterprises can scale up or down to the desired level of processing power and storage space easily and quickly.
Potential ability, power, and Capability
At this age of data explosion, today’s companies are processing 1,000 times more data than they did only a decade ago. With the proliferation of social media, 80 percent of the world's data is unstructured, and unorganized tweets, likes, videos, photos, blogs such data cannot be analyzed by traditional methods. Big Data platforms like Apache Hadoop have the capability to analyze all available 3V data. And the cloud makes the whole process easier and more accessible to both large and small enterprises.
Inexpensive and Affordable
One of the benefits of cloud computing is pay-as–you-use i.e., pay for the resources company need to store and process Big Data. In the pre-cloud era, businesses had to invest large sums of capital to purchase the necessary hardware. In order to allow for future data needs, companies typically overspent, buying more hardware than they actually required for accomplishing the task at hand. With the advent of cloud-based computing, companies can choose between hosting expensive on-site servers---which may need to be managed by IT teams or simply purchasing scalable space on demand and only paying for the storage space and processing power they actually use.
Momentum and mobility (2M) to sustain Speed and Agility
Enterprises with traditional infrastructure used to get a new server up and running. But the real costs of time delays lies in interrupted innovation. Cloud-based services allow companies to provision whatever resources they need---as they need them. In fact, a cloud database allows hundreds and even thousands of virtual servers to be deployed smoothly and seamlessly in minutes.
The era of Big Data has arrived. And cloud capabilities are taking Big Data analytics to a new level. As the technology is more affordable and accessible to enterprises in a variety of industries, the benefits of cloud-based big data analytics will become increasingly apparent as more and more businesses get on the cloud.