Table of Contents
Data continues to win as the most important asset for any type of organization, regardless of size or field of operation. But, as with any raw material, without the right refining process, it is difficult to extract the real value out of it. Even more so, with the right tools in place and implemented properly, data can be combined, augmented, and re-used to create repeated value.
“Data is the new oil” is a very ubiquitous quote and many people use it to stress the importance of data in modern business activities. The original statement was from a UK mathematician, Clive Humby, and he coined it in 2006 as follows: “Data is the new oil. It’s valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc. to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value.” While this statement remains true more than 12 years later, data can now be augmented and its value increased over time. The original metaphor is no longer enough to describe data’s full potential.
“Data is the new Oil” is no longer enough to describe data’s full potential to create value for your organization.”
Next-generation analytics tools and infrastructure are necessary to unleash the abundant potential of data. The last decade has delivered more diverse and powerful computing devices, not only general purpose X86 CPUs but also ARM for power-efficient edge applications, joined by incredibly powerful GPUs and FPGAs for high intensive data and image computation or real-time data stream analysis. Additionally, storage is much more affordable than it was in 2006; as well as, faster, scalable, and globally accessible through standard web-based protocols. The revolution does not stop there, computing models have changed as well, with serverless computing and containers increasingly chosen for their elasticity and their ephemeral behavior taking advantage of consistent external storage resources for data persistence.
IoT, edge computing, machine learning (ML), and artificial intelligence (AI) are generating huge amounts of data, but this is only a small tap into full reservoir:
- Data must be stored safely and for a very long time.
- It should be easily and quickly accessible across all geographies.
- It should be shareable on any device via standard interfaces.
All of this is desired while maintaining high-security standards and controlling costs to remain competitive.
Object-based cloud storage is the key to the realization of a new data-driven cloud paradigm, but cloud storage services are not born equal.