Your Data Migration Checklist [Tick’em Before Migration]

Are you fearing data loss?

Yes! That's a big area of concern when you initiate data migration. But the great news is you can tackle that. All you need to do is follow some parameters before you initiate the migration process.

Here we'll discuss the data migration checklist that you can follow to make the process smooth and faster.

Let's get started!

Deploying the best practices of data migration is important to shift data from one database to another. But before starting to migrate the database, here are some matters you need to check;

Prior to migration, you need to analyze your data thoroughly. Every data point, process, and pain point needs to be checked before starting the whole thing. Once your data gets migrated to another data storage, it will become hard to retrieve it. Hence, you need to have a comprehensive view of your database. A complete assessment of your data processes can help you understand where you now stand.

Now, after assessing your data, you need to find the key scopes of the migration process. It should have a clear goal and strategy for the migration tasks mentioned beforehand. Besides finding the project scope, you have to consider the timeline, budget, and assignment team as well.

Experiencing the same thing again in the new database after migrating the entire database is not just right. You want to experience a seamless flow into your new database, right?

For that, you have to understand the current state of your data. Only then can you improve the situation. You have to stop pushing bad data into your system at any cost. If you can identify bad data, then you can easily remove it. Applying the data cleansing procedures can help you at this stage to make your database free from bad data.

Before moving forward with the data migration process, you have to ensure that your database is clean and compact. By doing so, you can end up getting a clean database after the completion of the data migration process.

Having a good team for handling the data migration tasks is very important. You need to choose the right people for your team who have good experience in managing data migration. Besides skills, you also have to decide the size of your team for the migration project.

All your stakeholders must have a representation in your team. It means you need someone from each department to team up for the data migration project. For example, people from the sales team best know about the CRM data. Similarly, your operations teams best know your ERP than other members of your organization. Hence, before you start migrating your data, you need to seek assistance from these teams that are going to work with the same data after the migration process.

Allotting a project manager is necessary for the successful implementation of any data migration project. A dedicated project manager is solely responsible for wrangling all the stakeholders associated with the migration project. Also, they ensure the project gets completed within the specified budget without any waste.

Above all, the involvement of the leadership or the management is essential for the migration to happen. Leaders of the organization must stay in the loop during the migration period. Because they are the ultimate decision-makers regarding the migration thing.

Let's accept the fact that data migration requires support from all our teams to happen. It's a collaborative thing, and for that, all your team should be on the same page. Defining the data migration objectives in clear terms and setting all goals aligned with the migration should be there. Setting the priorities of the migration project helps keep the team aligned with the project objectives.

It's the responsibility of the project manager to keep everyone updated on the priorities of the project. They must possess a solid communication plan to connect the team and proceed with the migration.

During the migration, the quality of the data can be compromised. Data loss is also among them. 58% of companies have faced data loss incidents because of migration failure in the past. Hence, the quality of the data should be checked at each step during the migration process. Even before the migration, you have to ensure you have prepared a solid data backup by your side. Therefore, the chances of getting back the old data will be high there even if the data gets stuck during the migration.

For quality maintenance, you need to install a sharp quality parameter within your data system. The data you insert into the database must be fed into the system consistently and thoroughly. It should be standardized and updated for optimal benefits.

Anything new that happens in the data ecosystem must be done through a proper plan. A dedicated project manager is vested in framing a proper implementation plan for the migration. Besides framing the plan, scheduling for every event is also there. Like we discussed already, data migration is a collaborative thing, and it demands a detailed plan for its proper implementation.

Every person involved in the migration project must receive the plan before they start with the migration. Every person should also receive relevant training for performing the data migration. So that it won't create any trouble during the actual data migration. Everything can be done within time and with measures.

Data migration nowadays can be done via software (AI-Powered) within a very specific time. Tools can perform the migration tasks faster, but are unable to provide accuracy or any quality assurance at all. They just follow the formula and the ways they were built (by some AI developer). The chance of data loss and degrading the quality is still there. Hence, you should always focus on getting your migration projects done via human assistance.

Data migration via AI+Human collaboration in its best at this point. Before you start the migration, you need to think about it for once.