It’s no longer a debate as to whether businesses should migrate their data to the cloud. To date, over 60% of corporate data is stored in the cloud, a twofold increase over the last seven years. For many organizations, drafting and executing a data migration plan from on-premises to the cloud opens a new business world of increased flexibility, optimized operating costs, heightened security, and continuity in the event of a disaster. A data migration plan is an all-around strategy with a clear roadmap on how to move business information from one environment to another. A typical plan highlights the approach and execution, and validates the overall data migration process to ensure a smooth transition. The primary role of creating the plan is to ensure the process of moving data is safe and secure without disrupting normal business operations. But even so, trusted industry insights reveal that organizations are still struggling with making the transition more effective —only 36% of data migration projects are executed within the forecasted budget, and only 46% turn out to be successful within the set deadline. While it’s commendable that some companies are able to conquer the last mile of data migration and drive desirable business outcomes, these numbers subtly show a dismal success rate. So, how do you create a successful data migration plan from the onset? Here is an in-depth guide on how to conduct a data migration with careful planning. We also highlight prevalent methodologies and the common mistakes to avoid. Let’s dive in. Types of Data Migration There are three types of enterprise-wide data migration approaches, including: 1. On-Premises to Cloud Data Migration On-premises to cloud data migration is the process of moving business information from the organization’s local infrastructure, such as in-house data centers and servers, to a cloud environment. Implementing cloud migration is a go-to option if your company wants to enhance business agility and flexibility. With your applications and corporate information in the cloud, employees can access important resources from anywhere, facilitating new engagement models, such as remote collaboration. Moving business information from on-premise storage to the cloud is also a viable approach if you want to attain greater scalability and resource optimization. This is because cloud computing allows your company to scale or cut down storage and computing resources as much as required, depending on the prevailing market demand. Additionally, this translates to switching your business model from capital expenditure to operational expenditure, which can significantly cut operating costs in the long run. Another benefit of migrating corporate data from on-premises storage to the cloud is assured disaster recovery and business continuity. Depending on your cloud partner, you can access robust backup and recovery solutions for mitigating cybersecurity concerns and downtime in the event of a disaster or complete system failure. 2. Cloud-to-Cloud Data Migration While many businesses are in the race to migrate to the cloud for the first time, some companies have been there for years and might consider exploring the prospects of a new service provider. As the name suggests, a cloud-to-cloud data migration approach entails moving unstructured business data from one cloud storage to another. On a small scale, look at it as transferring business files from Google Drive to Dropbox or any other combination of cloud storage platforms. Implementing a cloud-to-cloud data migration strategy is ideal: When diversifying or mitigating vendor risk: It makes sense to consider switching to another cloud platform if you want to negotiate better terms and mitigate vendor lock-in risks. Also, you would consider the move if the target service provider offers specialized services that give your business an upper hand over the competition. When optimizing operating costs or performance: The target service provider you’re eyeing might offer optimized performance features at relatively cost-friendly paid plans, prompting you to switch. Again, the need to negotiate better service-level agreements (SLAs) that are commensurate with the value of your money might also drive you to take this approach. When meeting regulatory or compliance requirements: You might want to migrate your business data from one region to another within the infrastructure of the same service provider to meet certain compliance and regulatory requirements. This approach is especially viable if your business branches out to a jurisdiction with stringent data governance and sovereignty laws. 3. Cloud to On-Premises Data Migration Cloud to on-premises data migration entails transferring an organization’s digital assets, such as corporate data, business applications, and workloads, from a vendor-owned cloud platform to local infrastructure. While shifting from cloud to on-premises solutions is uncommon in the modern business landscape, you might find the approach to be a viable option in specific scenarios, such as: Changing business needs: Every business is unique and may undergo changes from time to time. In some cases, the foregoing business need might demand the organization to gain more control over corporate data or applications. And if you want to meet those requirements or customize the infrastructure, moving the data to on-premises might be the suitable approach. Regulatory compliance: In certain jurisdictions or highly regulated industries, governments and compliance bodies may require organizations to store sensitive customer data or applications on-premises. In that case, migrating from the cloud to local storage will ensure that you comply with these laws and provisions. Cost optimization: Although switching to a cloud environment offers immediate business benefits like flexibility and scalability, there are some cases where the long-term costs cut into the benefits. And if that’s your present situation, going back to the on-premises infrastructure might translate to cost-saving opportunities. Prevalent Data Migration Methods Another critical aspect of migration planning is choosing the right data migration methodology. While this ultimately depends on the intricate needs of your company and the goal you want to achieve in the long haul, there are basically two options when it comes to data migration techniques. They include: Big Bang Migration Also known as the cut-over approach, Big Bang migration entails moving all business data from the current storage to a new environment in a single process. Owing to the scope of work involved in this technique, it’s important to plan extensively and coordinate effectively for a smooth transition within the shortest time possible. In fact, doing it as fast as possible should be the goal, given that the technique involves shutting down the entire system and operations before implementation. Because of this risk, Big Bang migration should be implemented during off-peak hours, such as public holidays or weekends, when you least expect customers to use the system. The risk also makes the technique suitable for smaller organizations that serve a regional clientele base and relatively want to move smaller amounts of data. In other words, it’s not suitable if your business model cannot sustain a complete system downtime at any moment. Trickle Migration As the name suggests, the trickle technique is an approach involving phased or iterative data migration steps. Unlike the Big Bang technique, the trickle migration approach allows you to transfer data in small increments while the business system is still operating and running concurrently with the migration process. The same also applies to IT functionalities, allowing you to migrate gradually over time and make adjustments in the course as much as needed. But while this technique reduces the impact on operations and enhances proactive risk mitigation, it has drawbacks as well. For instance, the costs of maintaining parallel operations in the source system and the target environment while moving data gradually can add up pretty quickly and overrun your budget. You might also have to deal with co-existence complexity when it comes to integration or managing data synchronization. For these reasons, the technique is suitable for enterprise organizations that can’t afford any system downtime. A Step-by-step Process of Data Migration Understanding the data migration process is another critical aspect of successful planning. While this may vary depending on the amount and type of data that you want to transfer, here is a typical process of data migration: Step 1: Identify the Data Format, Location, and Sensitivity The first step involves identifying the type of data that you want to migrate, as well as its current location and level of sensitivity. By having a clear understanding of this information, you can plan for the migration with robust security measures in mind and prevent critical errors from happening during the process. Step 2: Define the Project’s Size and Scope After establishing the properties of the data to be migrated, define the scope of the project, duration, and budget. Establishing clear goals around these parameters will help you plan and execute the migration effectively. It will also help explain the whole process to the non-technical C-level executive and business stakeholders. A data migration plan template can be used to organize these details Step 3: Backup All Data Ensure that you back up all data, preferably in multiple locations, including cloud storage. By doing so, you’ll be able to retrieve original files, especially if you encounter technical challenges during or after the migration. This may include missing, corrupted, or incomplete files. Step 4: Assess the Requirements Needed for Successful Migration A typical process of moving data from a target source to a new environment can be demanding. Assess whether you have all the necessary resources — personnel, tools, and technology - to complete the migration on the first attempt. At this stage, you should determine whether you need to hire experts or acquire third-party tools Step 5: Execute the Data Migration Plan Following your detailed data migration plan, start executing the process by allowing the right system permissions required to extract information from the source and export it to the preparation environment. This will allow you to clean the data and transform it into the required format. Then export the clean data to the target environment and monitor the process throughout to identify and resolve any technical glitches that may arise. Step 6: Test After executing the actual migration, it's important to ensure that all data was moved from the source to the target environment without any loss of connectivity between the systems involved. To account for this, it will help if you conduct several high-level tests, from the system and unit to volume, batch, and web-based application evaluations. Step 7: Audit, Validate, and Implement Maintenance Even with successful testing results, it's important to conclude the migration process with a thorough audit of the system to validate whether the project will truly yield the benefits of a cloud-first strategy, such as cloud native development. To validate this, watch out for any missing, incomplete, or corrupted data set and restore the respective files from your backup. Best Practices for Data Migration Planning Now that you understand the typical process of data migration, what are some of the best practices to have in mind before commencing the project? Best practices entail acceptable and industry-recognized guidelines, techniques, or methods developed on the basis of extensive research and proven experiences. To ensure that the process is as seamless as possible, with the highest degree of success, it will help if you: Set Up a Dedicated Team to Manage the Project As noted earlier, data migration can be a complicated process, especially if you intend to move voluminous data sets from legacy system sources. Given the dedication and attention that this project requires, it’s prudent to set up a dedicated team to oversee it from the start to the end. The team can comprise your in-house data engineering experts and any other external specialist required for successful implementation. Backup All Data Before Migration Another best practice for data migration is backup. By backing up the data in multiple locations where you can easily retrieve it, you’ll be assured of business continuity in the event of a disaster or cyberattack. And on top of protecting your information from getting lost during the migration process, backing up the data gives you the luxury of rollback capabilities. This means you can always revert to the pre-migration state and fine-tune the plan in case the first attempt doesn’t go as intended. Raise the Quality Standards of the Data The main reason why you’re migrating from on-premises storage to a cloud environment is probably to enjoy the benefits of the cloud-first approach, such as scalability and advanced data analytics services. However, this won't be possible if you migrate poor-quality data. With this in mind, it is crucial to identify and rectify any quality inconsistencies before moving the data. This will improve data integrity and overall decision-making processes to help you harness new business opportunities in the future. Establish Data Governance Establishing data governance practices to guide the project during, before, and after migration is important, especially if you’re going to maintain data quality assurance. Data governance enactment also establishes stewardship and agreed-upon responsibilities, ensuring 100% accountability when it comes to risk management and data protection. Moreover, establishing data governance puts you on the good side of regulatory compliance, especially in stringent provisions such as the General Data Protection Regulation (GDPR). Conduct As Many Tests as Needed Lastly, data migration isn’t a plug-and-play tech process, especially if you're moving enterprise information in iterative phases. To ensure that everything goes as intended, test the migration process at every phase, from planning and design stages and execution and maintenance. The goal is to ensure that all risks are accounted for and the process runs as smoothly as possible. Common Data Migration Planning Mistakes Prevalent mistakes to avoid when creating a data migration plan include: Not involving business users from the start: Business users should be involved from the onset because they possess valuable insights into the type of data that is set to be migrated, its quality, structure, and level of importance to the organization. If you fail to involve business stakeholders, user acceptance and adoption rates will drop drastically after implementation. Not preparing your source data: Analyzing the source data for thorough cleaning and preparation streamlines the overall migration process and guarantees data quality in the target environment or system. Inconsistent data preparation will not only result in integrity issues but also extend timelines and increase costs. Not establishing sustainable governance: Data governance helps you establish the frameworks for overseeing data management, security, and compliance beyond migration. Neglecting sustainable data governance from the onset can result in long-term repercussions, such as security loopholes and data integrity concerns. Not testing and validating: Testing and validation are critical aspects of data migration planning as they help you identify any potential issues that may jeopardize desired results post-migration. Failure to test the plan, the migration will likely end in data loss, improper data mapping, or extensive database corrupting, ultimately bringing business operations to a standstill. Wrapping Up It’s important for organizations to consider their unique position in terms of data security, compliance, performance, and scalability before creating a comprehensive data migration plan and executing it. Additionally, it’s prudent to seek professional guidance from cloud migration experts, especially if you’re going to avoid common planning and migration mistakes in the first round.