The Right Time to Manage and Analyze Big Data in the Cloud

  • There are lots of variables from the method and cost of connectivity to the infrastructure you have on-site to how varied your big data workloads are.
  • Analyzing Big Data in the Cloud to Boost Business
  • Scaling Resources Automatically

If you’re about to take an analytic crack at unfiltered terabytes or even petabytes of complex, unstructured data, it can stay in a public cloud provider like Amazon Web Services, said Judith Hurwitz. The consultant and author of numerous IT books, including several in the For Dummies instructional series, said analyzing big data in the cloud often works “because you’re still in the process of separating the wheat from the chaf,” so there’s no reason for the extra security of keeping it in-house. “It has not become mission-critical at that point,” Hurwitz said.

“Companies will be more likely to then move their data into a private environment, into the data center, into a private cloud, because those are now the crown jewels.”

But once you complete your analysis and have your unique, core data, bring it back on terra firma. Private cloud computing, especially the sort that is built in a company’s data center, is the preferred place, she said. “Companies will be more likely to then move their data into a private environment, into the data center, into a private cloud, because those are now the crown jewels.”

There are lots of variables, Burke said, from the method and cost of connectivity to the infrastructure you have on-site to how varied your big data workloads are. “Is it something where you’re running roughly the same volume of information through your system and you’re maintaining roughly the same volume of data in storage all the time – or does it fluctuate wildly?” Burke said.

ANALYZING BIG DATA IN THE CLOUD TO BOOST BUSINESS

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.

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.

By using the cloud, even small firms can have success in leveraging information, analyzing big data to assess markets, evaluating customer needs, and planning new products and services.

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.

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.

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