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5 Best Practices for Flawless Data Migration and Different Migration Approaches


Plenty of databases and the day-by-day increasing volume of decisive data make it highly possible for organizations to plan a data migration process at some point in time. Data migration is the processing of moving their existing data into stronger or more functional data storage and processing system. By default, data migration is a highly complex and time-consuming process. For someone who is planning for data migration, it is important to accomplish this process flawlessly to ensure that there is no loss or damage to their data and allied systems, as well as no downtime. In this article, we plan to discuss ideal data migration strategies, the processing include, and what you need to consider while planning for enterprise database migration. Let us explore.

Why do enterprises plan for data migration?

There are many reasons why people plan for database migrations. Some such instances are:

  1. To replace their existing servers with more functional ones.
  2. To transfer the on-premise infrastructure to a cloud or distributed environment
  3. To update the existing database with a new, more functional one.
  4. Due to a merger or acquisition by another corporate.
  5. To move the data to another new CRM.

Unfortunately, a study shows that more than 70% of the data migration projects fail to fully and flawlessly meet their migration objectives. This makes it crucial for the technology decision-makers and data migration project administrators to understand and follow the best practices in data migration to ensure that this process is accomplished smoothly.

Data Migration

Data migration best practices

Further, let us overview the top data migration best practices as recommended by the experts.

  1. Do not miss out to back up your data

As we have seen above, even when you are confident about your system’s upkeep, there are times where it may not go accordingly to your plan. So, before you initiate the first step of migration of your data, ensure that you have a proper backup of your valuable data to a secured server and can retrieve it anytime if needed. With the data backup handy, if any problems arise and you end up incomplete or corrupted with the data migration project, you can easily restore your data to the previous state with it.

  1. Verity the quality and complexity of your data

Another best practice to follow in data migration projects is to verify the complexity of your data. Understanding this will help you to identify the best approach for data migration suiting your data needs. Always assess the various forms of organizational data and make sure which data and databases you plan to migrate, where it is situated, and how and where it is stored. Identify its current format and also into which format it may get changed after migration. Along with the complexity and format of data, also identify how clean your data is. Check the quality of t and identify it requires any updating. You may try to conduct a data quality assessment with providers like to identify the quality of your legacy data stores and think of separating good data and eradicating duplicates. 

  1. Agreeing on the data standards

Once you know the complexity of your data and the quality of the same, you can think of putting in some migration standards. To identify the problem areas and avoid any potential unexpected issues during the migration process, you can take adequate measures by following the standards you put in place. In any case, data is fluidic, and the form of which can change continuously. So, having proper standards in place can help you with data consultation, with which you can ensure that your data is fully useful in the future. This will help safely migrate your databases and ensure that it meets the desirable standards to be useful over time.

  1. Analyze your current and future business rules

While dealing with customer data and databases, you have to ensure compliance with the regulatory guidelines. So, it is essential to define the current business rules and future scope of the same to plan for appropriate data migration projects. All these compliance measures should be in tune with the business rules and validation to ensure that your data remains consistent and useful. Based on the primary analysis, you need to come up with a custom set of rules for the data before migration and then re-evaluate the rules and increase their complexity if needed once the migration is done.

  1. Have a foolproof data migration strategy

Once the previous steps are followed properly, the next step is to build a proper data migration strategy. There are two basic approaches one can take for data migration as:

  1. Big Bang migration, and
  2. Trickle migration. 

In the Big Bang approach, the entire data transfer is done within a given timeframe, like 24 hours or 48 hours, etc. The live systems may be down during the period when the data is going through the ETL processing and further gets on to the new database. This is a quicker migration approach, but riskier too.

In Trickle migration, the data is split into two different stages split across the old system and new system concurrently. The major advantage of this approach is that there is no downtime, as in the case of the Big Bang. Even though this approach is much more complex, it is deemed much safer as data is continuously migrated.

Considering all the above, you need to understand that data migration processes may require the involvement of various teams inside the organization. You need to ensure that the process is communicated properly with all the involved team members and their doubts are cleared. They should know what to expect and what to in case of any adversities to avoid any chaos. You also need to assign the responsibilities and tasks to each one involved properly. Also, make sure that that you have the right resource in place to accomplish each task successfully. 

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