With so many firms getting involved in big data strategies given the relative ubiquity of accessible solutions, the best practices of management and optimization are beginning to transform and evolve. One of the key matters in this discussion has been the increasing need for flexible, speedy and reliable computing power to back the storage, processing, access and uptime demands of analytics strategies, and the cloud has thus far proven to be a champion in this regard.
Cloud computing quickly became one of the more popular approaches to IT infrastructure, platform and software overhauls nearly a decade ago, and has been a critical driver of big data adoption, especially among companies that did not have access to these highly scalable models. Despite the fact that so many aspects of big data are gaining traction in the cloud, there appears to be plenty of room to grow and progress from a management and optimization standpoint.
Opportunities to improve
InfoWorld editor-in-chief Eric Knorr recently published a blog regarding the potential opportunities involved in migrating big data to the cloud, but affirmed that many companies have appeared to be relatively averse to this concept. He stated that the process of moving big data can be a highly expensive prospect, which is why so many firms have ruled out doing so regardless of what the cost benefits might be once it arrives in the cloud.
However, this does not necessarily need to be the case, as so many enterprises are already using the cloud for backup, disaster recovery and other data hosting strategies. According to Knorr, the information being stored in these environments can indeed be used within a big data strategy so long as the right steps are taken, and larger enterprises might have a little more ground to cover in these projects compared to smaller firms. After all, the latter group has been a bit more aggressive in their embracing of the cloud for these purposes.
In the coming years, the author argued that "continuous capture of data" and the process of analytics streaming are likely to gain more traction after somewhat of a slow start, and that this might lead more firms in the direction of migrating intelligence frameworks into cloud-based computing environments. With all of the trends that are taking shape today, it will only make sense to truly embrace the cloud for big data hosting purposes.
"Hyperscale computing is becoming critical."
More reasons for cloud
The cloud helps to reduce the strain big data would otherwise place on backend systems, all the while making the analytics strategies more flexible in and of themselves. Hyperscale computing is becoming critical given the prevalence of the Internet of Things, enterprise mobility, rapidly diversifying corporate operations and the ever-expanding universe of data being generated, shared and analyzed around the globe.
Even if firms launched a big data strategy outside the cloud computing arena, it might be financially and operationally advantageous to begin migrating into these environments.