Moving your data to the cloud can help manage costs and increase agility. In the cloud, you can scale up or down as needed to handle spikes in demand and control costs. The cloud also offers more choices 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.
Peter Choe, Data Practice Lead, Ippon Technologies USA, and Shawn Johnson, Solution Architect, Matillion, chatted on a webinar about the right strategies and tools for moving to the cloud. Here are some of their top tips for a successful cloud implementation and migration.
When building a data strategy, it’s important to examine your people, processes, and technology closely. When you understand your organization's current state, you can develop a strategic plan for its future state.
People
When looking at your people, you need to understand the skill sets your employees already have. You don’t necessarily want a strategy that forces everyone to re-skill. Building off your employees’ existing skills will allow you to pivot to the cloud more quickly and better assess which gaps to fill immediately and which skills to develop over time.
One great way to identify all your existing skills 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, including whether they need to be responsible, accountable, Consultable, or informed on particular initiatives. For instance, you might designate a Data Engineer Consultant to be Consulted for data-related initiatives.
Processes
Understanding how your existing processes intersect is important so that when you move one thing to the cloud, you understand what else might be impacted. You can create a strategic migration plan with a thorough understanding of your existing processes.
Technologies
Numerous technologies can easily be migrated from on-premises to the cloud. For example, Unix and Linux scripts can easily run on cloud platforms, and SQL is used extensively in both.
Again, assessing existing technologies can take advantage of your employees' skills. Research to determine if you can move your existing technologies over or if there’s a better technology option available in the cloud.
If you want to move your business to the cloud, you need buy-in from everyone, from low-level developers to C-level executives. Everyone needs a clear vision of the project's goals and should support the overarching cloud transformation strategy.
When talking to developers, you may want to discuss day-to-day efficiency and ease of management. Data teams are overloaded, and increased productivity is an immediate benefit. When talking to C-level executives, you’ll want to focus more on the big picture and business value: future development, speed to analytics, ROI, delivering value to end consumers, and the actual dollar value of the project.
When migrating to the cloud, avoid the “Big Bang” approach. Start small. Doing so can help quickly demonstrate the ROI of moving to the cloud. Starting small also helps developers build their confidence in working with new tools and technologies.
If you start with smaller, more tangible projects that yield immediate business value, you’re more likely to reinforce the importance of a bigger initiative. Also, in your first endeavor, you’ll undoubtedly run into bumps in the road that require you to correct course. These shifts are easier to make on a smaller project.
The majority of organizations employ three common methods for moving to the cloud for their first cloud migration: lift and shift, re-platforming, and refactoring. Additionally, some organizations may opt to engage a Data Engineer Consultanting team to assist in the migration process, providing expertise in handling data-related aspects of the transition.
Lift and shift
Lift and shift, or load and transfer, is exactly what it sounds like: you basically move an application and its associated data to the cloud as-is, with no redesign. When you are just beginning to learn about the cloud, lift, and shift might be the easiest, fastest, and most cost-effective way (in the short term) to get an existing on-premises application or process moved to the cloud. It’s also a great way to become more familiar with the cloud.
Load, transfer & sync
This is similar to lift and shift, but once you’ve loaded and transferred to the cloud, you then try the available cloud services and swap them out for increased efficiency. For example, you might move your application to the cloud but swap out the database for a cloud-native database. With this approach, you can benefit from cloud services' automated backup and operations.
Re-architect and re-platform
This approach requires the most time and effort. It involves reimagining how your application will run on a cloud platform and then re-designing it to take advantage of cloud-native capabilities fully.
This method may be useful if your current architecture is unable to scale to meet future business needs. It can also help you achieve cost savings over lift and shift in the long run. However, this method is the most time-consuming and difficult upfront.
All the major cloud providers offer a variety of managed services and components that you can use to expedite your move to the cloud. Review the marketplaces for each provider to determine if they offer the applications and microservices you need. Some providers also offer a cloud adoption framework to help support your cloud migration plan.
Even as you choose a provider, remember that you may need to make a change at some point in the future or need a multi-cloud strategy. Consider ways to make your applications cloud-agnostic.
Whether you are performing data transformation or simply loading data into the cloud, cloud-native ETL products can help you increase productivity and accelerate time to value. Trying to adapt on-premises ETL tools and processes to the cloud won’t take advantage of the platform’s speed and scalability, as a cloud-native solution will.
Matillion supports all the major cloud data warehouses, and it provides a graphical, low-code/no-code user interface that can generate SQL for you. Pre-built connectors help you get your data into the cloud from common data sources, and the ability to ‘Create Your Own Connector’ using REST API ensures that you can bring data into the cloud from virtually any source. Data teams are overloaded, and Matillion helps them move faster and more efficiently, increasing the speed of analytics.
The cloud is an ever-evolving technology; your data journey will continue to transform alongside it. Even after the completion of your cloud migration, known as post-cloud migration, it's important to recognize that the cloud environment remains dynamic. Your move to the cloud will likely be a gradual process, and you may still maintain some on-premises applications for an extended period.
To ensure ongoing success, it's crucial to be prepared for continuous evaluation of your services, both within and outside the cloud. This evaluation allows you to identify areas for improvement, enhance efficiency, and harness the benefits of new and emerging technologies. Regardless of where your data resides, whether in the cloud or on-premises, staying vigilant and adaptable enables you to optimize your data management strategy and leverage the full potential of evolving technologies.