Understanding Data Migration: Strategy and Best Practices
What is Data Migration?
Data migration refers to the act of moving data between systems. This may seem quite simple, but it requires a change to the application or storage.
In the context of the extract/transform/load (ETL) process, any data migration will involve at least the transform and load steps. This means that extracted data needs to go through a series of functions in preparation, after which it can be loaded in to a target location.
There are many reasons why organizations perform data migrations. They might need to overhaul an entire system, upgrade databases, establish a new data warehouse, or merge new data from an acquisition or other source. When a system is being deployed alongside an existing application, data migration may be necessary.
A Data Migration Strategy is Vital
No matter what the purpose of a data migration is, it’s generally designed to improve performance and increase competitiveness.
You have to do it right.
Less successful migrations can result in inaccurate data that contains redundancies and unknowns. Even if the source data is complete and accurate, this can still happen. Any issues in the source data may be magnified when they are incorporated into a more advanced system.
A complete data migration strategy prevents a subpar experience that ends up creating more problems than it solves. Incomplete plans and missed deadlines can lead to migration projects failing. Teams must give migrations their full attention when planning and strategizing. They should not be subordinated to other projects with a larger scope.
These are the critical elements to consider when creating a strategic plan for data migration.
- Understanding the data A complete audit of source data is required before migration. If this step is not taken seriously, unexpected issues could arise.
- Cleanup Once you have identified any problems with your source data, they must immediately be corrected resolved. Due to the size of the job, this may require third-party software and tools.
- Protection and maintenance Data can become unreliable over time due to degradation. This means that data must be protected data quality.
- Governance It is essential to track and report on data quality in order to gain a better understanding of data integrity. This information must be easily accessed and automated wherever possible.
A data migration plan should not only include a step-by-step process, but also a process to bring in the appropriate software and tools.
Data Migration Strategies
There are many ways to create a data migration plan. The specific needs and requirements of an organization will determine which strategy is best. However, most strategies fall under one of these two categories: “Big Bang” or “Trickle”.
“Big Bang” Migration
The full data transfer can be completed in a short time frame with a big bang migration. While data is processed and transferred to the new database, live systems are affected by downtime.
This method has the advantage that everything happens in one event and takes very little time. However, the pressure can be intense as the business is limited in its ability to use one of its offline resources. This could lead to a compromised implementation.
Consider running the migration process prior to the actual event if the big bang approach is most beneficial for your company.
“Trickle” Migration
Instead, trickle migrations complete the migration process in stages. The old and new systems are implemented simultaneously, eliminating downtime and operational interruptions. Real-time processes can ensure data migrations are continuous.
These implementations are more complex than the big bang method. If done correctly, however, this added complexity can reduce risks rather than increase them.
Best practices for data migration
No matter which method of implementation you choose, there are best practices that you should remember:
- Before you execute, back up your data. You can’t afford data loss if something goes wrong during implementation. Before you move forward, make sure that backup resources are available and that they have been tested.
- Stay true to your strategy. Too many data managers create a plan, then drop it when it doesn’t go as planned or when things get too complicated. You should be prepared for the fact that migration can be difficult and sometimes even frustrating. Stick to your plan.
- Test, test and test again. You should test your data migration during the planning, design, implementation, and maintenance phases to ensure that you achieve the desired result.
Six Key Steps to a Data Migration Strategy
Every strategy is different, depending on the company’s goals and needs. However, the general pattern of a data migration plan should be the same.
Explore and Assess the Source
Before you migrate data, it is important to understand and know what you are migrating. You must understand how much data you are pulling in and what that data looks.
Some data may have many fields. However, not all of them will need to be mapped into the target system. You may have missing fields in a source, and you will need to pull data from another location to fill the gap. You should ask yourself what data fields need to be moved, what can be left behind and what may be missing.
You should also audit the data within the system to ensure that you are meeting all the data transfer requirements. You might reconsider migrating the data if there are insufficiently populated fields or a lot inaccuracies, incomplete pieces, or other issues.
The result of an organization skipping the source review step and assuming a thorough understanding of the data could lead to wasted time and money in migration. Worse, the organization could run into a critical flaw in the data mapping that halts any progress in its tracks.
Define and Design the Migration
Organizations decide what type of migration they want to undertake in the design phase. This includes defining the technical architecture and detailing the migration process.
Once you have established the design and data to be pulled over and the target system, it is possible to begin to set timelines and address any concerns. The entire project should be documented by the end of this step.
During planning, it’s important to consider security plans for the data. Every data that is important should be covered in the plan.
Build the Migration Solution
It is tempting to think that you can approach migration with just enough development. It is important to do the job right, as you only have one chance to implement it. One common strategy is to divide the data into subsets, and then build one category at a given time. Then test it. It might be a good idea to test and build in parallel if you are working on a large-scale migration.
Conduct a Live Test
After testing the code in the build phase, the testing process doesn’t end. To ensure that the data migration design is accurate and complete, it’s important to test it with real data.
Flipping the Switch
Final testing will be completed before implementation can begin according to the plan.
Audit
After the implementation is live, create a system for auditing the data to verify the accuracy of the migration.
Software for Data Migration
It is difficult and time-consuming to create data migration tools and code them manually. Data tools that simplify migration are more efficient and cost-effective. These are the factors to look for in a vendor when you begin your search for software solutions:
- Connectivity– Does the solution work with the software and systems you use now?
- Scalability How much data is the software able to store and what data will be needed in the future?
- Security Investigate the security features of a software platform. Your data is your most valuable resource, so it should be protected.
- Speed What speed can the platform process your orders?
Migration of data to the cloud
Increasingly, organizations are migrating some or all of their data to the cloud in order to increase their speed to market, improve scalability, and reduce the need for technical resources.
Data architects used to be responsible for deploying large-scale server farms on-premises in order to preserve data within an organization’s physical resources. One reason to move forward with the on-site servers was security concerns regarding the cloud. However, as major platforms adopt security practices putting them on par with traditional IT security (and necessarily in compliance with the GDPR), this barrier to migration has largely been overcome.
The right cloud integration tools help customers accelerate cloud data migration projects with a highly scalable and secure cloud integration platform-as-a-service (iPaaS). Talend’s suite of open source, cloud-native data integration tools enable drag-and-drop functionality to simplify complex mapping, and our open-source foundations make our solution cost-effective and efficient.
Get Started With Data Migration
A data migration is a possibility if your company is looking to upgrade systems, move to the cloud or consolidate data. This is a huge and critical project that must be done correctly to ensure the integrity of data.
