2.5 quintillion bytes of data. That’s how much we create each day. This would fill 10 million Blu-ray discs, the height of which stacked, would measure the height of four Eiffel Towers on top of one another. It shouldn’t come as much of a surprise that the enterprises are hurtling into an era of data- driven business opportunities. It’s the world where data is not only the new oil. It’s the new soil on which business models germinate, profits bloom and competitive advantage is reaped.
But if an organization has to wring the benefits out of big data, it should follow a very assiduous approach. The key to success of big data processing lies in running it on an elastic infrastructure.
Big data with its ever-increasing volumes and lightning fast pace of generation demands a large number of servers, high network speed to sustain parallel processing and increased storage capacity for the vast swathes of data. In order to obviate this excruciating pressure on servers, storage, and networks, CIOs have started to trust the cloud as a panacea to their data management woes.
On-Premise Data Management Is Like Juggling on a Unicycle
Data management applications are ideal for deployment on top of cloud computing infrastructure. On-premise data management entails a huge upfront cost, both in hardware and in software. A cloud-based big data management platform can trim the costs of managing and scaling big data. With the huge amount of data needed to be stored and assessed in-house, your organization will require large data centers, which are not only prohibitive to manage but incredibly difficult to scale.
As the business expands, it accumulates more data, requiring you to grow your data center along with it. When the volumes of your organizations’ big data expand, it becomes tougher and less practical to manage it on-premises. It's almost like drinking from a fire-hose. Here a cloud-based platform will meet your data scaling needs aptly. So deploying data analytics on the cloud is a viable proposition for large enterprises.
A KPMG research survey predicts that by 2020, at least a third of all will pass through the cloud. The cloud paradigm is gaining widespread acceptance as a preferred platform for the development and testing of new analytics applications and for the processing of big data that is generated outside the four walls of the organization. The flexibility of the cloud together with its elastic scalability enables crunching humongous volumes of unstructured data to identify patterns and extract data-driven insights.
Running the big data analytics on the cloud makes a sound business sense for SMEs and start-ups as well. With its pay-as-you-go-pricing model of the cloud along with reduced manageability headaches, the cloud could well be the answer to their prayers. Resource availability is typically elastic, with a seemingly infinite amount compute power and storage available with on-demand model.
Cloud Helps Unearth Nuggets of Gold
In addition to saving money, cloud-based big data analytics can provide better value for your data analysis. It lets you deep dive and get a clear view of the story that lies within your data. Being on cloud eliminates your dependence on on-premises software to access data analysis tools. This boosts seamless access to all users across departments at any time and from any location. This dismantles data silos and allows them to dig deeper into the data analysis process. This is in turn considerably improves your organizational insights and creates more successful outreach, promotional and amplification campaigns, and better business opportunities.
Cloud-based big data management also promotes consolidation and collaboration. It enables all lines of business within an organization to collaborate, share and reference data to derive better results without the physical limitations of meetings and coordination.
The different departments within any organization collate, generate and analyze their own data, creating data silos and no single version of truth. When the cloud platform is married with big data management, data integration is baked into the big data strategy. Without data silos and single version of truth, you can leverage data to its fullest capacity and gain greater value from its well-rounded analysis.