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Big data environment requires a bunch of servers that processes large volumes, high velocity and various forms of big data. IT organisations increasingly consider cloud computing as a platform supporting their big data projects. While companies usually keep most of their sensitive data private, large volume of information like that on social media may be accessible externally. Thus; analysing where data resides, either internal or over public clouds makes big data far more appealing in terms of both cost and swift access to details!
With sheer percentage of amorphous data from social media, more value can be hauled from big data structures sets that are aligned and evaluated to achieve a competitive edge. An undeniable fact is that data is too big to process and transfer anywhere; it’s simply the analytical program that requires shifting, not raw or processed information itself! That’s possible with public clouds as most open data sets like Pinterest, weather, Facebook, Twitter, genome datasets and cumulative industry-specific information residing in the cloud is far more cost-effective. Enterprises find it quite lucrative to cultivate the information and cloud itself.
Factors that drive big data over cloud platform
Cost reduction
Cloud computing provides a lucrative solution supporting big data technologies and advance analytics programs that drives cost and business value simultaneously. Organisations are always eager to unlock the full potential of what’s hidden in data to compete at their level best. IT industries should consider cloud computing as an ultimate platform to save additional expense with ¬pay-per-use model.
Reduces operating cost/overhead
In order to implement big data solution, various components and their integration is required. Cloud computing transform such components entirely automated thus reducing operational intricacy that eventually boost IT team productivity.
Speedy provisioning
Provisioning cloud-based servers is far easier like buying something over the web. Big data settings can easily be scaled up or down as per processing requisites. Quick provisioning is crucial for relevant applications as value of data deteriorates with time.
Suppleness
Huge computing power in short time is required when big data analysis is in the books. For such analysis, servers need to be mobilised in matter of minutes. Such scalability and flexibility can be achieved through cloud tech that relieves you from those tedious investments on super computers. You simply pay for computing service on hourly basis.
Big data analytics
The very term “Big Data” refers to huge data sets recognised for their magnitude (total volume). These are far more diverse, structured, unstructured (assortment), advance and speedy than anything you or your organisation have yet dealt with. This stream of information is generated from interconnected devices such as PCs or smartphones to sensors such as traffic cameras and RIFD readers.
Being heterogeneous; it comes in various formats including text, image, document, video and much more. The real value of big data is derived from details it produces when assessed such as discover patterns, indicator for decision making, derived meaning and tendency to act in response to the world with much greater intelligence. Big data analytics is an assortment of advance technology designed to deal with various information sets. Quantitative methods such as robotics, computational mathematics, artificial intelligence and neural networks are a few ways to manipulate date and discover their relations and flow patterns.
Initiator of Big Data analytics – The cloud
Big data analytics and cloud hosting/computing are the two primary initiatives that rule industrial minds across the globe. Big data analysis offers the promise of catering precious details giving competitive advantage, sparks innovative ideas and a means to increase profit for companies. Being an IT delivery model, cloud computing carries the potential to augment business agility and output with less cost expenditure plus greater efficiencies.
Unlock the full potential
Various cloud models helps accelerate potential for a range of analytics solutions. They offer efficiencies and flexibility when it comes to access data, drive value and deliver valuable insights safely. However, these aren’t a one-size-fits-all solution as organisations choose from several cloud computing options as per their infrastructural and operational needs.
Leveraging workload, security cost and data operating ability, IT administration within an organisation may opt for private cloud thus minimizing risk and regulate full control. Other options can be public cloud to enhance scalability or hybrid model with combined attributes of both public and private cloud.
Cloud technology matures
Cloud computing today is a reality for many businesses with private cloud deployment mostly taking the lead. Such technology has matured over time while addressing barriers against adoption with improved security and data integration. IT industries mostly benefit from such technologies with evolution of cloud services and integration. For instance, a survey performed in 2013 by Ubuntu revealed that more or less 55 percent considers cloud a perfect fit for mission-critical workload.