Moving Data to the Cloud: Seven Tips to Choose Strategy and Tools

Moving  data to the cloud can help manage costs and increase agility because it enables you to scale as needed for demand variations while simultaneously controlling costs.

The cloud offers more choices—and oversight—for SaaS applications. Cloud provider marketplaces are filled with tools that can help you move your data, transform it, analyze it, and meet just about any other need you have. Here are some tips to keep in mind for a successful cloud migration and implementation.

1. Choose a cloud strategy that starts with people before processes and technology.

Any project that doesn’t begin with an accurate current state appraisal will encounter extra challenges—including some that may lead to failure. So when building a data strategy, it’s essential to understand the existing state of your people, processes, and technology before deriving  a strategic plan for a future state. Your solution will be most successful when you begin with the people who will be using it.

Start with people

What are the skill sets your employees already have? A strategy that forces everyone to re-skill will be time consuming, risky, and may tank employee morale. Building from team members’ existing skills enables a faster pivot to the cloud. You’ll also have a clearer picture of which gaps to fill right away and which skills to develop over time.

One great way to identify existing skills within your organization is to build a RACI chart. Also known as a responsibility assignment matrix, a RACI chart shows the skills, roles and responsibilities of your employees: Do they need to be Responsible, Accountable, Consulted, or Informed on particular initiatives?


How do your existing processes intersect? Evaluate this so that when one thing moves to the cloud, you understand what else might be impacted. With a thorough understanding of your existing processes, you can create a strategic migration plan. Unclear about your processes? A good place to begin is with a Strategic Data Assessment.


How cloud-friendly are your existing technologies? Numerous technologies can easily migrate from on-prem to the cloud—for example, Unix and Linux scripts as well as SQL.

Assessing existing technologies ties back in to people. Leverage skills team members already have and research to determine if you can simply move your existing technologies over or if there’s a better technology option available in the cloud. Expert input can help.

2. Bring the entire organization on board.

It may sound obvious and simple, but a move to the cloud requires buy-in from everyone from entry-level developers to the C-suite. Give everyone a clear vision first of the benefits, then of the project’s goals.

Developers will resonate with the day-to-day benefits: efficiency and ease of management. Increased productivity immediately gives relief to overloaded data teams.

The C-suite responds to big picture business value: speed to analytics that provide actionable insights, true ROI, delivering value to end consumers, and how the scalability of the cloud supports future growth plans.

3. Small steps achieve quick wins.

As anyone who’s ever taken up a new exercise regimen somewhat over-enthusiastically can attest, a fully immersive “big bang” approach can have painful consequences. Start small. Small steps bring quick wins to demonstrate the ROI of moving to the cloud. Starting small also helps developers build up their confidence working with new tools and technologies.

Smaller, more tangible projects that yield immediate business value reinforce the importance of the larger initiative. As in any new endeavor, you’ll run into bumps in the road that require course correction. That’s easier to do with smaller pieces of the project.

4. There’s more than one way to move to the cloud.

What’s your best method? Here are three common methods of moving to the cloud that the majority of organizations employ for their first cloud migration:

Lift and shift

Lift and shift, or load and transfer, is exactly what it sounds like: Moving an application and its associated data to the cloud as-is, without redesigning anything. Lift and shift is probably the easiest, fastest, and most cost-effective way (in the short term) to move an existing on-prem application or process to the cloud—especially for first-timers. It’s  a great way to become more familiar with the cloud.

Load, transfer, and sync

Similar to lift and shift, this method entails an additional step. Once you’ve loaded and transferred to the cloud, you can test different available cloud services for increased efficiency. For example, you can move your application to the cloud and swap to  a cloud-native database. This approach enables benefits from cloud services’ automated backup and operations.

Re-architect and re-platform

If your current architecture is unable to scale to meet future business needs, this approach is appropriate. It’s rethinking the way a specific application should behave on a cloud platform, then redesigning it to take full advantage of cloud-native capabilities.

For organizations in a state of limited scalability, this can achieve cost savings over lift and shift in the long run. However, this method is the most time-consuming and difficult up front.

5. Choose the right cloud provider for your needs.

All major cloud providers offer a variety of managed services and components that can speed up your cloud migration. Some  also offer an adoption framework to help support your cloud migration plan. If you already know  the applications and microservices you need, it’s easy to compare providers. But if not, an IT assessment can help.

There’s no way to predict the future, but expert help can make your cloud migration flexible for when you might need to make a change or grow to need a multi-cloud strategy. Consider ways to make your applications cloud-agnostic.

6. Cloud-native data loading and ETL speed up time to value.

Whether you’re performing data transformation or simply loading data into the cloud, cloud-native ETL products make a difference for productivity and value. Adapted on-prem ETL tools and processes aren’t nearly as fast and scalable as their cloud-native counterparts.

As an example, Matillion supports all major cloud data warehouses and has a SQL-generating graphical, low-code/no-code user interface. Pre-built connectors move your data into the cloud from common data sources. You can also create your own connector using REST API, enabling you to bring in data from virtually any source and increasing the speed to analytics that provide actionable insights.

7. Keep running.

Everything evolves. Just as the cloud isn’t static technology, your data journey will continue to evolve as well. If you’re moving to the cloud gradually, you may maintain some on-prem applications for years—and that’s fine. Regardless of your approach, continually evaluate your services both in and out of the cloud to improve efficiency and take advantage of new and emerging technologies wherever your data lives.

Learn more about planning a move to the cloud.

To learn more about selecting the right strategy and tools to support your cloud transformation, check out our Strategic Data Assessment solution or contact us directly. We’re happy to provide more links to articles, research, or answer your questions on moving to the cloud.

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Originally published  November 16, 2021. Updated April 19, 2024.



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