As the world is witnessing a huge transformation at the technological front, organizations are constantly upgrading their legacy systems to keep up with the trend. Though updating to new systems is the need of time, a major challenge lies in migrating data without losing it. Hence, it becomes important to plan out an efficient data migration strategy to ensure that migration happens without any data loss.

Testing of migration is as important as migrating data; failing to do so, organizations may face issues of discrepancies causing expected results, which can affect the organization adversely. Furthermore, to carry out efficient migration testing a well-defined strategy is required, without which the organization can be left financially drained of resources after setting up more processes than they need. They may even find that their commercial success is negatively influenced by not exploiting their data to the fullest.

What is Data Migration? Why Do Organizations Undertake Data Migration?

The process of moving data from one system to another, preferably from a legacy system to a new one, is known as data migration. However, the process is not as straightforward as it may seem because it involves a change in storage and database or application. The data migration process involves three defined steps extracting data, transforming data, and loading data. When the data is extracted from the sources, it must go through a series of cleansing to eliminate errors and inaccuracies to qualify the data for efficient analysis and load them to the targeted destinations.

Organizations perform data migration for varied reasons; first, as a part of their system revamping plan, the other possible reason could be during the upgrade in databases, while another possibility could be when creating a new data warehouse or merging data from acquisitions. But it’s most common when teams are deploying other systems alongside their existing applications for integration purposes.

Why is Data Migration Strategy Important?

A comprehensive data migration strategy comes in handy when performing large-scale operations that need to preserve business continuity simultaneously. Organizations perform data migration to improve performance and competitiveness. When organizations carefully control the data migration process, they can prevent delays caused by missing deadlines or exceeding budgets, while improperly managing the process can leave a lot of migration projects dead in their tracks. In planning and strategizing the work, teams must ensure that they put their best foot forward with undivided focus on one project.

Data Migration Strategies

There are several approaches to developing a data migration plan, however, the two major data migration strategies include “big bang” or “trickle.”

• ·         ‘Big Bang’ Data Migration

Organizations follow big bang data migration to ensure that the data is moved from the legacy systems to the target destination and the full transfer is done in a limited time. As the data migration process goes through the three inevitable steps of extraction, transformation and loading, the active system may experience a little downtime towards transitioning to the new database. The data migration process has some challenges like validation implementation failure, lack of data analysis scope, and inability to validate specification to name a few. But companies implement this strategy as the entire process of data migration takes less time to complete even with many challenges

• ·         ‘Tickle’ Migration

Tickle migration is conducted in phases to avoid downtime or operational interruptions. In addition, migration staging is conducted continuously to support migration, even during peak operations.

Key Components in Data Migration Strategies

Moving sensitive or important data isn’t a simple task as it involves a lot of aspects that would need consideration. Hence, it is not a good idea to begin the process without having a plan on how this should be done. One must consider the key components of data migration strategies based on the critical factors mentioned below.

• Knowledge of data — It is critical to have adequate knowledge of the source data to find the solution to issues that may arise unexpectedly. Hence, consider doing a thorough audit of the source data before migration.
• Data cleansing — Between source data extraction to data transformation, there is a critical step of data cleaning, which focuses on identifying the issues of source data and resolving them.  The data cleaning can be done using software tools and third-party resources. 
• Data quality maintenance and protection — The quality of data may subside over a period. It is critical to maintain and protect the data quality to ensure the reliability of the data migration process.   
• Data tracking and reporting — It is critical to ensure data integrity by data tracking and reporting. Use the right tool and automate the function wherever needed.  

Although we can follow many ways to move data, it is important to have adequate knowledge about the best practices to ensure that the process of data transfer is done systematically and seamlessly.

• ·         Solid Planning

Good planning is half work done. Decide the systems that will need to be migrated and plan how they will affect the business. When migrating data from one system to another, always ask yourself if your changes can be made without affecting or hindering other systems already being used by the business. Solid planning will help in carrying out the entire process with utmost ease.

• ·         Action Steps

It’s time to give your migration process a ticking clock and a detailed, step-by-step plan– including the plan of execution – what, who, why, and deadlines – to ensure your migration is successful and time-bound.

• ·         Crosscheck

Decide what technology to use for the migration and how it will fit into the larger IT ecosystem. Make sure you have a plan in place for decommissioning old systems.

• ·         High-Quality Conversion Process

Ensure you map out the technical details related to how you plan to move data. Then, put processes in place to ensure that your data stays organized and of high quality.

• ·         Build & Test

Here, you will implement the software logic that performs the conversion of data. Test the script in a mirror sandbox environment instead of running it against your production database.

• ·         Execute

You’ll need to verify that data migration processes are safe, reliable, and fit for use in your business before implementing them.

How to Make Your Data Migration Go Smoothly?

Transferring sensitive data is a complex yet delicate process. However, here are some best practices to follow to ensure a successful migration.

• ·         A Thorough Migration Plan

It would help if you had a good idea about how much data to move, from where it will come, and an idea of how you’re going to implement its move into your target server or location. Your plan should outline each necessary step and who will be responsible for them, physical aspects such as technical or compatibility issues, downtime expected for your system, and the source data and migration tools if they are going to be used. Last but not least is protecting your data’s integrity. Backups may prove exceptionally helpful in preserving your original data.

• ·         Examine your Data

Before you proceed, take a close look at the data that you’re going to be migrating. In particular, identify and weed out data that is outdated and no longer important. Separating it from your migration will help streamline your process and set a clean slate for your team after the migration is complete. If there are pieces of information that require security controls due to the nature of its regulatory information, make sure you take these details into account.

• ·         Put Migration Policies in Place

A data migration policy ensures that your data is on the right path after it’s been migrated. It also organizes and gives control over who will handle it and how they will do it, along with adequately protecting your company’s sensitive data.

• ·         Automatic Retention Policy

Once you’ve successfully migrated, you must take the time to ensure that everything is placed where it belongs and remains safe and secured. It’s essential to keep all your systems in working order by setting up automatic retention policies to prevent data leakage. Also, make sure that outdated data has been validated and permissions are granted accordingly. Finally, just ensure that old legacy systems will back up automatically in the event of any technical difficulties – but make sure to double-check them before they’re put on standby!

Conclusion

As technology continues to change, businesses must continue to evolve as well. As a result, companies must create a plan for their data and understand data migration in today’s business world. Data migration can be challenging, but a company can migrate its data with minimal downtime and stress with a proper strategy and a few best practices.

At Yethi, we have the expertise of handling complex financial data migration, with pre and post-migration testing along with regular audits. We offer the most efficient end-to-end testing service. Our test automation platform, Tenjin, can test large data migration easily and efficiently while reducing time and cost significantly.