Your business is considering moving its analytics platforms to the cloud—but you’re unsure if the time is right. You might have concerns around security, cost, or maturity of analytics solutions in the cloud
. On the other hand, these solutions have developed rapidly over the last few years, and some of your partners (or even competitors) may already be leveraging the cloud for analytics. Is it the right time for you to move? Let’s break down a few factors that may have you considering a cloud migration sooner rather than later.
If Scalability Is Becoming Critical
Constantly changing business requirements and the rapid pace of innovation have made it difficult for organizations to anticipate the amount of infrastructure needed around analytics. When the limitations of on-premises infrastructure are impeding your organization’s ability to scale quickly to meet needs around processing power or capacity, it’s time to plan your migration. Cloud analytics platform providers such as Teradata offer a competitive edge through the ability to flex as your analysts’ or data scientists’ needs expand.
There are plenty of use cases where short-term scaling of either storage volumes or processing power can offer tremendous value to your business. For example, you might be kicking off an exploratory data science project that constantly joins large tables together to produce a result, leaving few computing resources left for the loading and reporting already taking place on the platform. In the cloud, your infrastructure can be quickly scaled up for the few weeks (or months) it takes to complete the project before scaling back down and reducing costs.
If You’re Already Storing Data in the Cloud
“Data gravity” is a term used to describe how data on a certain deployment often attracts additional applications and services. If your business is already leveraging the cloud for application infrastructure, and subsequently storing app-based data in the cloud, then it’s often not only cost-effective but also shortens development cycles when moving your analytics to where this data resides. Public cloud solutions such as Amazon Web Services charge data egress fees that can add up quickly when moving data out of that environment. For example, if you’re storing a significant amount of application data in AWS S3—and running ETL jobs that push this data to your analytics tools on-premises—you’ll be surprised at the costs associated with doing so. If your analytics platforms reside in the same cloud deployment, however, then these egress fees will not apply.
Teradata in the Cloud
Teradata is leading the cloud analytics space with powerful analytics and elastic scalability. Not only do we offer flexibility for users to choose where they can quickly deploy a Teradata environment—on both AWS and Microsoft Azure, as well as our own infrastructure—we’ve been working hard to offer new capabilities that make it fast and easy to scale when needed. With Teradata in the cloud, you can now scale compute and storage independently in mere minutes. You can also stop and re-start the database to save on compute costs during off-periods.
A wide variety of enterprises are leveraging Teradata in the cloud to run their full production workloads at scale—and they’re winning. A quick search for “Teradata” on the Azure or AWS Marketplaces will get you started on deploying Teradata right away—and let you begin seeing how quickly your business can also win with cloud-based analytics.
To learn more about Teradata in the cloud, I encourage you to follow the conversation at #CloudExperts
, or reach out to your Teradata account executive.