By now, most people with some technical savvy have wrapped their heads around “the cloud.” It’s not an abstract, ethereal data center floating around in the great above. It’s simply using a server, not your computer’s hard drive, to push and receive data across the Internet.
Four advantages of cloud computing
Scalability: As you add users and increase your storage demands, you do not need to buy added physical equipment and servers. Scaling is done by moving to a bigger machine or adding resources to an existing one…or moving to a smaller machine and removing resources. In many cloud setups—scaling up is automatic.
Performance: On premise data servers and facilities are more prone to downtime and hardware failure. Cloud providers generally offer redundancy across multiple facilities, significantly reducing the risk of downtime. Other benefits include improved security, accessibility, and continuity.
Flexibility: With more of the workforce remote, the cloud is well suited to host a virtual environment. Resources can be allocated instantly, backup data and systems can be activated remotely, and new applications can be deployed quickly.
Value: Although an initial investment is needed to prepare and migrate data to the cloud, over time there is significant savings—from both a maintenance and staffing standpoint. And with 58 percent of IT leaders saying infrastructure is a growing drain on resources (Dynatrace, 2022), it’s no surprise that cloud computing and intelligent infrastructure monitoring platforms are becoming standard.
Tips for planning your cloud data migration
Having extolled the benefits of migrating your data architecture to a cloud environment, let’s set the stage for what you should expect. It should not take months. It should not require a large team of data experts. It should not be stressful. But you need the right plan, and the following five factors can help you achieve it.
- Understand your use cases. Be specific about the value you will gain. Identify what data points you can leverage to make different or better business decisions. How you plan to use data should influence your infrastructure. Using it strategically will elevate your return.
- Assess your existing data and environment. What is the volume of your objects, and do you have large datasets? Are the legacy and cloud environments compatible? You’ll want to optimize your migration. Being able to answer these questions will help you set the right strategy.
- Determine the time and resources needed to migrate the data. The goal is to keep time and resource usage to a minimum and to have 0% data loss. If the legacy system is supported, you can use a platform migration tool. Other options include ETL tools or customizing a process. Each has advantages and disadvantages. Also, be sure to consider connection speeds available to your organization. To migrate 10TB of data would take 100+ days with a 10Mbps connection speed; at 100Mbps, it would take 10 days.
- Plan for testing and sign-off. Separate the migration and UAT into several groups. Testing everything at once is overwhelming, and if an issue is found, the migration process starts over. To stay on task, iterate and test one group while the next is migrating.
- Have an after-migration plan. Repointing reports and setting up new data processes in the cloud will take time. It can sometimes take months to fully implement all business rules, ETL, and other processes. Consider developing a transition plan to keep cloud data up to date until the transition is complete.
Migrating your data architecture to a cloud environment can offer a measurable return on investment in speed, efficiency, ease of access, and cost savings. Planning will ensure your time and resources will produce the expected results. If you’re not sure where to start, a partner like Garnet River and our cloud and infrastructure team can help.
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