Big Data has led to an explosion of information across the web. Organizations today are generating up to 2.5 Trillion gigabytes of data every day according to a recent survey. This enormous generation of data is presenting management issues under a traditional framework. Not only storage of huge dataset pose a problem, analyzing the large sum of data to take out only the most useful bits is equally gruelling. Moreover, these large sets of data often carry sensitive information like credit/debit card numbers, addresses and other details, which raises data security concerns. Hence, CIOs are facing the question on how to manage and secure the essence of this data rather than just stacking it?
Companies wanting to innovate faster with Big Data should consider Cloud technology. Cloud computing can create numerous benefits for any given company. It is faster, cheaper, more flexible and easier to keep up to date. Also, a well-implemented and a well-thought-out cloud environment aids companies in driving innovation, thereby making Big Data analytics more impactful than ever.
In this article, we shall see in detail the benefits of using cloud computing with Big Data.
Using cloud computing for Big Data is not just for tech stars like Facebook and Amazon, but also more traditional companies. In the enterprise world, Big Data has now become essential, and if companies are utilizing the cloud, it allows them to easily track, analyse data and ultimately act on insights.
Combined, cloud computing and Big Data can offer tremendous value to all kinds of companies. Let’s take a look at those advantages.
A few years back Big Data processing used to be expensive and cumbersome. This meant that Big Data efforts were stative i.e it provides insights from out-of-date data. Businesses, however, are required to be proactive and able to access, analyse and act upon the most recent data. Basically, before the cloud, Big Data was a big effort. Cloud-enabled Big Data eradicates the requirement of hiring dedicated programmers just to run basic analyses, and moreover, there is no need for warehouses too.
With the cloud technology, companies implementing Big Data can quickly gather data from multiple sales, marketing, and web analytics, clickstream data, call centre, and inventory sources. Moreover, companies are not required to use their own massive servers but instead the cloud, companies facilitate data compilation, and analyse it, quickly refine it into a presentation, and then act on it. This helps in keeping IT costs low, while increasing flexibility and scalability.
The traditional infrastructure of storing and managing data is slow and hard to manage. It can take weeks to just install and run a server. Cloud computing facilitates organizations with all the resources you need to enable thousands of virtual servers and get them working seamlessly in only a matter of minutes.
Cloud computing is a blessing in disguise for many organizations. A company that wishes to have updated technology under a budget can certainly use cloud technology as it allows them to pick services they want and pay for it as they go. The resources required to manage Big Data are easily available and are less expensive. Before the cloud, companies used to invest huge sums of money in setting up IT departments and then they used to pay more money to keep that hardware updated. As cloud facilitates companies to host Big Data on off-site servers, they are now able to pay only for storage space and power they use every hour.
For a Big Data project, a company using cloud computing causes a significant change in the traditional approach to planning and utilization of resources. Ultimately, cloud technologies helps in encouraging and embracing a fast-moving, innovative environment where teams can utilize the cloud to store abundant amounts of data and discover new use cases for their data. Cloud computing and Big Data are still under constant evolution. Together, they have the power to provide a cost-effective and scalable infrastructure that supports Big Data initiatives and business analytics, thereby proving to be the ideal combination.