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Migrating Your Big Data to the Cloud

Michael Chen
Senior Manager

When people talk about big data, they mean pentabytes, sometimes exabytes of transmitted data, all containing countless critical records for a business. Some of this big data may come in structured from expected data sources such as transaction records or online forms, and some of it may be extracted in an unstructured way from social media feeds. Combined, that’s a lot of data, and hosting it all on premises can create numerous challenges.

Thus, it’s no surprise that the market has shifted towards a cloud-based solution, with either a complete shift to the cloud or a hybrid solution as the end goal. Getting there, however, takes some careful planning.

How much planning? On a recent episode of Oracle’s Integration: Heart of the Digital Economy podcast, host Kellsey Rupple talked with Chai Pydimukkala, senior director of product management for data integration. Kelsey and Chai went in-depth on the pitfalls and challenges of migrating data to the cloud.

Given those challenges, why migrate to the cloud? Chai breaks it down to three major benefits.

  • Security: Chai talks about how not that long ago, cloud security made a lot of people nervous. The idea of trusting an external source with all of your data seemed counterintuitive. However, today that has completely inverted. The organizations most at risk for data breaches seem to be midsize companies operating their own data centers, while cloud data services have invested in security—and they keep evolving those security protocols, as it is key to their business model. What does that mean for the current cloud data market? “Security should be the least of users’ concerns,” says Chai.
  • Performance: When you move your data to the cloud, you are handing the keys—and the maintenance—to someone else. But unlike onsite data centers, cloud services are built specifically to maximize performance. That means if you need more processing power or bigger hardware, it’s simply a request to the service, one that is often fulfilled expediently. This ensures that performance is always optimized and always scalable without draining your local IT resources.
  • Cost: When you scale upwards in a cloud service, there are usually associated charges with that. However, when placed side by side in comparison with the practical cost of scaling locally, the cloud is more cost-effective. It’s not just about purchasing new hardware, though that’s part of it. The scope of incurred costs includes new hardware, time lost by IT staff implementing new hardware, potential downtime during integration, and more. Cloud service scalability is the nature of that industry and expected. “You're not just looking at the capital expenditure to build a data center,” says Chai. “Think about all the headaches involved in maintaining the people, resources, and different teams to run the data center.”

When you consider these benefits, it makes sense that more and more organizations are moving their big data to the cloud. But what are the biggest challenges they face? To hear more about this journey, listen to the entire podcast episode Moving Data to the Cloud, and be sure to visit Oracle’s Big Data Blog to stay on top of the latest developments in the field of big data. Want the posts sent directly to your email? Subscribe to the Big Data Blog today!

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