Getting the right cloud architecture is crucial if businesses want their big data projects to be successful, according to CenturyLink.
The company says that while big data can be powerful, giving organisations extremely detailed insight for fast decision-making, it can require big processing power and storage requirements.
As a result, cloud architecture is increasingly becoming the go-to solution for big data needs.
"Many businesses now are looking to the cloud to meet their big data needs. The resources they could never hope to summon internally for challenging big data projects can often be easily obtained by using cloud-based data analytics platforms and applications,” explains Martin Hooper, big data and predictive analysis expert, Asia Pacific, CenturyLink.
Hooper says there are five key ways a cloud architecture can help make big data projects successful:
Flexible, elastic, and scalable infrastructure
The individual elements of big data infrastructure should have the flexibility to support multiple methods of integration with each other and external elements, Hooper says.
“Elastic infrastructure helps to ensure that projects can scale up and down as required, and cloud infrastructure is currently the best option for such elasticity,” he says. “Cloud makes it relatively simple to add or remove data analytics capacity on demand.”
Infrastructure availability and reliability
“As big data becomes an integral component of organisations’ everyday customer relationship management activities, it needs to maintain a level of availability and reliability that previously may not have been necessary,” explains Hooper.
“Big data is being wound into more and more core business activities and, like all core business systems, it needs to be available at all times. If it fails, revenue could take a hit,” he says.
High-performance computing with low latency
According to Hooper, big data workloads often function differently from traditional enterprise applications, and speed is essential in almost every deployment.
“Infrastructure needs to support these speed requirements,” he says.
“High-bandwidth, low-latency connectivity is ideal to deliver the required speeds. Cloud infrastructure can usually deliver this kind of capacity.”
Secure, compliant big data infrastructure
Big data requires big security and, often, stringent information management rules to meet regulatory requirements, Hooper says .
“The ramifications of falling short on either of these fronts can be serious and far-reaching,” he says.
“However, cloud-based big data infrastructure can usually deliver a consistent level of data security and information management standards to ensure all requirements are met,” Hooper explains.
A manageable big data ecosystem
Hooper says most cloud management tools offer infrastructure managers the ability to handle big data efficiently.
“These tools make it possible for managers to stay on top of shifting big data configurations to help ensure performance and efficient infrastructure use,” he says.