9 best practices for a successful data migration project
You certainly know that data migration projects are famous for their budget and time periods.
At first, data migration seems easy. Its false simplicity makes it very easy for project managers to underestimate this part and take care of the latter, only at the end of the IT project. Analyzing issues related to migration at the end of the project and not at the beginning, very often leads to serious failures.
About 70% to 90% of the data migration projects, do not meet the time and budget requirements which were set at the beginning.
Our advice applies to all types of migration, whether you want to perform a “Big Bang” migration or a “one-time” migration, while replacing your content management system for example or while redesigning your application/ website, or for an architecture review of a platform etc. As experts in offshore IT development, we would like to share some of the best practices with you, that will help you focus on the stumbling blocks of this kind of project and become more efficient, within your company.
Let’s go over these 9 points, one by one:
1. The importance of analyzing data complexity in their environment
Analyze the complexity of data and its impact. In this kind of project, one always comes across unforeseen events. The difference between success and failure lies is in the approach you choose to address while tackling these issues. Examine and evaluate the different forms of data to migrate. Where are they stored? How do they look when they reach their destination? How is the existing data, and how will they be after migration?
2. Define the norms
Once you have assessed the complexity of the data, we recommend that you define a complete set of standards. Setting standards allows you to quickly identify the areas with issues. This allows you to anticipate several problems, that you will be able to avoid before the final phase of the migration. Moreover, as data evolves over time, establishing a set of rules and standards can be very useful for making organization-wide recommendations and supporting data consolidation, within the information system of the company.
3. Clearly define the business rules in terms of now and the future:
Defining the business rules which shall apply to your data migration must address the use of your current data and the use of your future data, after migration. These rules must be compatible with the various rules, for validating and managing your information system.
4. Establish the governing rules of data
You can establish data governing roles by setting up a board of directors. The project manager will have beforehand, defined all the possible roles of the data in the information system. Therefore, each responsibility is attributed to each project member. It’s about who manages the information, who is responsible for the quality, use and data access. The purpose of data governance is to improve data quality and use.
5. Evaluate data quality
Data migration goes much beyond a simple migration, from point A to point B. Therefore, before transferring data from one system to another, you need to carry out a thorough data quality check. This helps evaluate the quality of existing data and creating firewalls to filter, cleaning and protecting the correct data, while eliminating duplicates.
6. Define risks related to data migration
Once the complexity of the data has been established, the standards are defined, and data governing structure has been implemented: Establishing the requirements, in terms of migration remains a fairly simple task. It is essential to thoroughly analyze how and where the organization’s data will be used and who are going to be the end-users, but also consider how this migration will change the way, end-users work in the future…
7. Evaluate and identify the right data migration tool
A good tool is a tool which is well supported by the infrastructure, in which it is integrated. This is why it is important to select a tool which is completely in keeping with the environment in which it shall be expressed. The ideal tool must be flexible and highly scalable, it requires minimal technical expertise and needs to be intuitive, so that technical staff and employees can work, collaboratively.
8. Implement a risk management system
During a data migration, a loss of data is inevitable. According to a survey, which was carried out in the United States, 57% of respondents said that they had a backup solution in place, just in case the data was lost during the migration process. 75% could not restore all lost data and 23% could not recover data.
Before beginning the migration process, it is strongly recommended to create a test environment and test out the migration process. This makes it possible to highlight failures and losses. Do not be hasty while selecting the tool. Choose a tool that can back up data and pre-set features, while managing the migration process, in a centralized console.
9. Migration and validation test
This is an essential step to validate the migrated data, in its entirety. Prepare precise test scenarios. This will allow you to properly test the migrated data. As for the migration of completed data, make sure you document each step of the migration process and maintain a clear audit document, to comply with regulatory compliance.
Sticking to these good practices will reduce the gaps and difficulties, associated with a data migration project.
Our developers have a sound knowledge on these best practices and can manage your migration project. Talk to us, about your migration project, our consultants will assist you in implementing a migration strategy. Whether it is for a software application development or web application, we offer our outsourcing services in Madagascar or Vietnam, to answer all types of IT or digital projects.
All the news, related to the outsourcing of offshore IT developments. Source: cygnet-infotech.com
