– Craig Sowell, Senior Vice President of Marketing, Datapipe
Some people might call big data the Jekyll and Hyde of today’s leading technology trends. On one hand, it’s been lauded for its potential to transform operations and drive revolutionary developments in a wide range of industries, including health care organizations, public works and innovators. On the other hand, people have made no secret of their concerns over Big Brother-esque invasions of privacy as well as information security concerns exacerbated by the mammoth volume of big data.
Whichever way you spin it, big data seems to be here to stay, and leading companies need to focus on making meaningful, responsible use out of their information resources. To do so requires the right IT infrastructure as a foundation – which includes both the secure environment for handling the data and the computing power required to turn a whole lot of facts and figures into something actionable.
It’s about the application
Big data in itself is neither good nor bad. It’s really about how you use it. Big data projects essentially come to naught if they remain just raw information. Instead, companies must utilize data – on any scale – to seek insights about products, people and the human experience.
Bigger scale calls for elasticity
Really, the main difference between big data projects and the type of analytics businesses and organizations have pursued all along is the scale and sometimes the increased variability of the information. To prepare for growing resources, companies need more robust infrastructures. Because of their scalability, flexibility and affordability, cloud services are well positioned to fill these requirements.
Cloud computing – and cloud-based analytics in particular – can be the differentiator that enables companies to separate out the critical, game-changing insights from the floods of generally meaningless factoids. These analytics can accommodate a business’ growing pool of information, which is being fueled by more convenient, omnipresent digital activities.
Ben Butler, senior manager of big data and HPC at AWS was recently quoted as saying: “It’s now dramatically easier and lower in cost to generate that data. It’s putting a bit of pressure on the rest of the lifecycle: collection and storage, analytics and computation. In the cloud we have a combination of different computer, network and storage tools you can use to address these issues.”
Cloud elasticity and on-demand provisioning not only enable the scalability organizations need from a service perspective, but they also provide the foundation needed for more insightful, real-time big data endeavors. Add to this analytics tools that help a company better understand cloud usage patterns across the organization, and cloud adoption becomes a value-add to help the organization achieve their business goals.