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Before your organization takes the leap of migrating your data warehouse or your data and analytics platform to the cloud, there are some key elements to consider. Having a good handle on your answers to these four questions will better prepare your team to make the move.
1. Why are you migrating your data and analytics platform to the cloud in the first place?
While this might seem like an obvious question, your answer should cover two things: what is the compelling event or reason for your organization to consider migrating your data to the cloud, and what do you want to achieve once it’s there?
In my experience, the answer to that first piece is widely varied. It might be that your organization’s data center hardware is reaching its end of life, end of support, or even end of lease, prompting a decision of some sort to be made. Sometimes it’s that you have reached a point where you have simply run out of hours in the night to do your data processing using your aging infrastructure. You can’t add more grunt to your hardware, and you can’t add hours to the clock, so you’re left with either buying expensive on-premises hardware or moving to the cloud.
Maybe it’s because you want to get your data closer to your apps that are already living in the cloud. Or perhaps you want to use machine learning and artificial intelligence to do predictive analytics on your data. To do that you need to be in the cloud.
Whatever your reasons, know what’s pushing you there and understand your goal. Having a good grasp on both can help you better articulate your vision to any partners you might have in your migration.
2. Are you considering a lift and shift or a full transformation?
Data migration isn’t always a cut and dried process. There are very legitimate pros and cons to either considering a lift and shift where you will have to try to retrofit improvements later or completing a fundamental redesign of your data, which means you’re starting from the ground up.
For example, a redesign will slow down your process initially, taking longer to get everything up and running. On the other hand, by simply moving what you have up into the cloud, you’re undoubtedly bringing along legacy issues that have been slowing you down. I liken the lift and shift method to packing up an old house and moving it into a new one. Most people find those final few boxes that they simply don’t have the heart to unpack, and that end up sitting in a basement or a garage. They’re probably filled with items that should never have made the move, but now that they have they’re just taking up space.
Whatever you decide, be clear on why you’re making that decision, understand the trade-offs, and go into the process with your eyes open.
3. Where is your IT organization from a skills perspective?
A company migrating its data and analytics platform to the cloud for the first time might make some stark discoveries, including a skills gap within the organization. Skills that are required for managing on-prem data centers differ from doing data analysis in the cloud.
Before you make the move to migrate your data warehouse, take stock of your in-house skill sets. Are there maturity gaps? If so, what’s your plan to bridge any gaps that you might discover? Do you intend to train up? If that’s the case, what time frame are you looking at? Do you need to hire data scientists? If you do, think about what specific skills you require and bring in talent early on in your process, so they have context for your new data environment. Don’t want to reskill or hire? Find a partner that can augment your team with managed services.
Understanding your team’s capabilities and capacity prior to migration will help ease the transition once you start operating in the cloud.
4. What’s your timeline and where do you want to begin?
Every journey starts with a first step, but many times organizations have no clue where to begin when it comes to migrating their datacenter to the cloud.
The best advice is to understand there are experts out there, like Quisitive, who have deep knowledge, great experience, and a proven methodology to help businesses like yours move your data and analytics platform to the cloud and get you where you need to go.
At Quisitive, we’ve developed a proven and prescriptive method for this very purpose: On-Ramp to Azure Data. It provides step-by-step guidance based on best practices and proven cloud adoption methodologies, tools, and resources, to migrate your data and analytics workloads to Azure. In a series of short sprints, it can rapidly move you from planning to use case execution in 30 days.
Data migration doesn’t need to be messy. By walking into the process with a clear vision, a strong plan, and the answers to these four important questions, your migration will roll out much more smoothly.
Click here to learn more about the On-Ramp to Azure Data program.
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