Explore the Most Useful Data Migration Strategies Today

Marketing Team
Published on December 12, 2021

For any business, data migration is a necessary practice, which is conducted on a regular basis. Having a good data migration strategy that assists companies is crucial for executive and information technology teams, whether it's building a new system or relocating information to more secure storage sites.  According to a recent Gartner Survey, 50% of all data migration projects exceed their predetermined budget due to a flawed strategy. So, let’s discuss some common steps to successful data migration.

What is Data Migration?

The process of transferring data between multiple file formats, databases, or storage systems is known as data migration. It's rarely merely transferring data from one system or database to another. More complex data migration methods, such as data mapping and re-formatting, may be required. Any data migration will include at least the transform and load steps in the extract/transform/load (ETL) process. This means that extracted data must be processed through a sequence of functions before being fed into a destination place.

Data migrations are carried out for a variety of reasons. They may need to completely redesign a system, modernize databases, set up a new data warehouse, or incorporate fresh data from an acquisition or other source. When deploying a new system alongside old applications, data migration is also required. Data migration can take several forms, including moving data to a new storage appliance to replace an old system or migrating from on-premises to cloud storage. You might also be replacing hardware in an application database, requiring data migration to new devices or equipment. There are a few key factors you need to take into account for any kind of data migration.

  • Data Integrity
  • Business Impact
  • Cost
  • User Experience and Impact
  • Potential Downtime
  • Data Assessment
  • Data Quality

What is the Difference between Data Migration and Data Integration?

While data migration and data integration may appear to be the same thing, they are not the same thing. You'll want to make sure you're using the right equipment for each job because each involves distinct methods and strategies.

Data integration is a set of technological and business methods for combining data from many sources and turning it into useful business information. This method helps with data analytics by aligning, merging, and presenting each data store to an end-user, and it's commonly done in a data warehouse using specialist integration software. In practice, ETL (extract, transform, load) is the most prevalent type of Data Integration.

On the other hand, Data migration is the process of moving data between different types of storage, formats, data structures, and corporate systems. Migration refers to the moving of data already held internally to different systems, whereas Data Integration entails obtaining data from sources outside of an organization for analysis. When a company implements a new system or merges to a new environment, data is often migrated. Migration techniques are frequently carried out by a set of algorithms or automated scripts that transfer data automatically.

Why is a Secure Data Migration Strategy Important?

Data migration occurs for a variety of reasons, but the most common reason is to improve the effectiveness and competitiveness of your IT operations as well as your broader business. Data that is better organized may be used more effectively, and data that is stored in one location in a single format reduces the need for — and cost of — many systems and hardware.

Poorly executed data migrations might potentially have serious effects. As a result, erroneous data, redundancies, and other errors may arise, requiring post-mortem correction. In truth, shoddy data migration can wreak havoc on data that is accurate, well-structured, and well-organized. A well-thought-out data migration strategy may help you prevent missed deadlines, financial overruns, and insufficient planning, all of which can lead to the project failing entirely. A comprehensive migration strategy also aids in keeping all stakeholders and team members on the same page, allowing them to complete duties more quickly and accurately.

Most significantly, your data migration method must be safe and legal. Noncompliance with cybersecurity and regulatory requirements could result in a data breach, as well as fines and penalties. Therefore, a strategic data migration plan needs to consider the following critical factors.

  1. Knowing the data: The source data must be thoroughly audited prior to migration. If this step is skipped, unexpected problems may arise.
  2. Clean-up: Any errors with your source data must be addressed as soon as possible. Because of the scope of the project, extra software tools and third-party resources may be required.
  3. Maintenance and protection: After a certain amount of time, data degrades and becomes untrustworthy. This necessitates the implementation of controls to ensure data quality.
  4. Governance: Data quality tracking and reporting are significant since it allows for a better knowledge of data integrity. The methods and tools used to generate this data should be simple to use and, if possible, automated.

Types of Data Migration

  1. Storage Migration: These migrations are concerned with transferring data from one storage device to another. It's possible to do this on-premises or in the cloud. Although storage migrations appear to be the most straightforward type of migration on the surface, you can't simply copy and paste 5TB of data. You'll need a well-thought-out strategy, as well as a grasp of where data is going and who should have access to it.
  2. Database Migration: When you migrate a database, you're usually upgrading the database engine and transferring the complete installed database of files to a new device. Database migrations are more complicated than storage migrations, as you're working with larger volumes of data that may be formatted differently. Back up the databases, disconnect them from the engine, and move the files to a new engine. After that, you can restore the files to the new database and location.
  3. Application Migration: This type of migration may include both database and storage migrations. When transferring an entire software application from one location to another, databases, directories, and installation files must all be migrated to a separate server, for example. You may also need to collaborate with the application vendor to take any additional measures that are specific to that product to ensure that everything goes smoothly after the migration.
  4. Wholesale vs. Incremental: While the types of data migrations listed above refer to the more technical aspects of the transfer, numerous strategic approaches to migration exist. You can use a wholesale method, in which the full migration is completed all at once and within a set time frame. You can also migrate data in stages and migrate incrementally. A wholesale transfer is advantageous since it is "one and done," whereas incremental migrations allow you to maintain your systems operational during the transition. To determine which technique is ideal for your company, you'll need to evaluate your business needs and technological plan.

6 Key Steps in a Data Migration Strategy

The specifics of each technique will vary depending on the organization's objectives and goals, but a data migration plan should generally follow the following pattern:

  1. Explore and Assess the Source

Before Migrating your data, you must know and understand what is it you are migrating and how you are going to use that. You must have a clear idea of the data you are migrating and how you want to fit in the target system. There may be a large amount of data with many fields, some of which will not need to be mapped to the target system. There may also be missing data fields within a source, necessitating the use of data from another source to fill in the gaps. Consider what you need to migrate, what you can leave behind, and what you might be missing. Run an audit on the actual data included within, in addition to completing the standards for data fields to be transmitted. If there are poorly populated fields, a large number of partial data pieces, inaccuracies, or other issues, you may want to examine whether you actually need to migrate the data in the first place.

  1. Define and Design the Migration

The design phase is where you have to design the migration course you need for your business. This step involves drawing the technical architecture of the plan and preparing a migration process. You can begin to identify timescales and any project problems by considering the design, the data to be pulled over, and the target system. The entire project should be documented by the end of this step.  It's critical to think about data security plans when planning. Protection should be threaded throughout the strategy for any data that needs to be protected.

  1. Build the Migration Solution

It's tempting to take a minimum development approach to migration. However, because you will only do this once, it is critical that you get it right the first time. Breaking the data into subsets and building out one category at a time, followed by a test, is a popular strategy. It might make sense to develop and test in parallel if an organization is working on a very large migration.

  1. Conducting a Live Test

It is the most important step to finalize your migration design. It is necessary to test your migration plan with real data so that you can ensure the accuracy of the implementation of your full-proof plan.

Common Data Migration Challenges and Solutions

Even with a well-thought-out data transfer strategy and plan, you should expect to face several obstacles and issues that are common to most migration operations.

Migrating Bad Habits: During data migration, some companies fail to pick out bad data, business, or IT practices. More particular, migration project managers may inherit corrupted files or data structures that, if migrated, will cause additional problems. Make sure you don't leave any bad processes or data behind when you switch.

Failure to Automate: Data migrations have a lot of moving elements, and a lack of automation and supporting software can cause the process to slow down or cause problems. To move data from one storage server to another, use tools like a data transport engine. While maintaining and updating file access rights, will save time and reduce overhead.

No Contingency Plan: Not having a backup plan for probable blunders is one of the most common data migration failures. You should approach data migration as if you were transferring huge sums of money from one bank to another. Data is extremely vital to any company, so you should map out potential failure areas and have a backup plan in place.