Last month's Google's GCP Next event illustrated the utility that applying off-premises computing and storage can bring to IT shops that are feeling the stress of trying to meet the rising need of data-driven analytics in the business.
IT embraces big data
IT has been increasingly pushed by executive leadership to support decision-making by analyzing big data in vast amounts, encompassing disparate sources and various formats. Given the low cost of online storage, keeping the data is not necessarily a problem, but doing something useful with large amounts of data can be daunting with in-house computing resources. Google has moved to address this need by combining a rich set of analytical tools with a cloud environment that can be applied flexibly to manage the data lakes that increasingly characterize business intelligence.
By using the cloud, however, even small firms can have success in leveraging information, analyzing big data to assess markets, evaluating customer needs, and planning new products and services.
As Google's CEO Sundar Pichai noted, computing is, in fact, addressing petabyte-scale problems. Google demonstrated several simple data sorts that involved petabyte-sized files during his presentation. Increasingly, such computing loads will be commonplace and the companies that can successfully manage big data applications will have a competitive advantage in the marketplace. However, until the advent of cloud-based advanced analytics and storage, such capabilities were simply out of reach for many businesses. By using the cloud, however, even small firms can have success in leveraging information, analyzing big data to assess markets, evaluating customer needs, and planning new products and services.
Of course, Google is not the only cloud vendor, or even the largest, but it has thought about the nuances of cloud applications. To that end, it has invested in machine learning and artificial intelligence technology to simplify the analysis of data. Moreover, it has made using these advanced routines as simple as tapping code that resides on a user's desktop.
Scaling resources automatically
Google has also taken pains to make its cloud resources scale automatically as demand ebbs and flows. Given its container-based computing architecture, it has made starting, stopping and troubleshooting applications simple and manageable. Google has also taken a comprehensive approach to security, incorporating both physical devices and digital tools to secure customer data.
For the IT professional who is worried about analyzing big data and supporting its application, the cloud would seem to be the perfect way to not only ensure that data lakes can be stored and protected but that they can actually be used. True, many applications don't lend themselves to a cloud environment and, for many, the need to manage a cloud partner relationship may be too much overhead, but applications that don't necessarily require on-premises control will benefit from a scalable architecture that is managed by someone else. Case in point: decision support.
decision support is increasingly identified in Frost & Sullivan surveys as the primary beneficiary of the fruits of analyzing big data. Whether or not IT is willing to integrate big data into the in-house computing solution set, executives will ultimately demand such capabilities as the market demonstrates the power of applying data to business decision making. So, the question is not if, but when. And the answer is now. Now is the time for IT to explore big data in the cloud. Cloud services providers like Google can help.
Next Steps
Business switch from defining to analyzing big data
