With the growth of new data types and the increasing volume of available data businesses need to implement analytics solutions to effectively extract the most benefit from the Big Data to which they have access. Meanwhile, data analytics is moving from batch to real time. This is particularly the case for predictive analytics, which can help the organisation to become future-focused.
Cloud is ideally positioned to provide the power and flexibility for Big Data analytics. Cloud computing itself has the potential to enhance business agility and productivity, while enabling greater efficiencies and reducing costs. Cloud and Big Data analytics technologies continue to evolve, and forward-thinking businesses are increasingly investigating both. A growing number of enterprises are building efficient and agile cloud environments that can process the large volumes, high velocity and varied formats of Big Data.
So, why move your analytics into the cloud? Here are three great reasons:
- Cloud-based Analytics-as-a-Service (AaaS) has the power, flexibility and scalability to cope with Big Data. That said, cloud-based Big Data analytics is not a ‘one size- fits-all’ solution; organisations using cloud infrastructure to provide AaaS have multiple options. The cloud platform might vary, depending on factors such as workload, cost, security, and data interoperability. IT might choose to utilise their private cloud to mitigate risk and maintain control.
- Businesses might prefer to use public cloud infrastructure, platform, or analytics services to further enhance scalability. Cloud service providers are offering various data analytics solutions to meet different IT needs – form MapReduce to more complex analytics packages.
- IT might implement a hybrid model that combines private and public cloud resources and services.
Servers based on the Intel® Xeon® processor E5 and E7 families provide the performance and data handling capabilities for many different Big Data analytics environments. Advanced storage capabilities are also available through Intel Solid-State Drives (SSDs), featuring high-throughput and high endurance. Additionally, Intel Ethernet 10Gbit Converged Network Adapters provide high-throughput connections for large datasets.
The bottom line is: no matter which cloud delivery model makes the most sense, businesses with varying needs and budgets can unlock the potential of Big Data in cloud environments.