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7 Data Migration Steps to Build Your Plan

 

With 99 percent of companies planning a move to the cloud in the next few years, odds are there’s a data migration project in your future. Whether you’re upgrading data storage, switching databases, moving to the cloud or adding a data warehouse, you need to be able to migrate your existing data safely and efficiently. As big data continues to grow bigger, data migration is becoming a routine part of data management. Migration is the process that’s going to get your data where it needs to go. Consider the following steps as you plan your next data migration project.

 

Step 1: Take an inventory of your data

 

To successfully move your data, you have to understand where exactly it is and how to access it. Take a complete inventory of all of the data that you need to move. Consider data locations, types of data you’re dealing with, and the format of your data in the source systems and in the target system. Determine if you will be migrating any potentially sensitive data, such as data containing personally identifiable information (PII) and take steps to make sure this data will be properly secured before, during, and after the data migration process. Work with data owners to gain access to the systems you need.

 

It’s also important to understand how all of your data impacts existing business processes. You want to make sure that you don’t break any existing processes during the migration process. Engage data owners in your project planning and work with them to ensure that the migration goes smoothly.

 

Step 2: Determine your timeline

 

There are a couple of different schools of thought when it comes to timing for data migration projects. You can migrate all of your data at the same time, which is known as a “big bang” strategy. The biggest benefit to this approach is speed. However, the trade-off is that this approach almost always requires system downtime. “Trickle” migration involves completing the project in phases, while running source and target systems in parallel. Migrating data incrementally will take longer, but it can usually be performed without having to shut down key systems. Trickle migration requires less downtime and provides more testing opportunities. It’s important to pick the data migration timeline that’s right for your organization and your users.

 

Step 3: Back up all of your data

 

Losing data adds a lot of stress and extra work to any project. So make sure that you have current, complete backups of all of your data before you begin moving the data around. If you encounter any problems during the migration, such as corrupt, incomplete, or missing files, you can restore this data from backup.

 

Step 4: Choose your team and tools

 

Migrating data can be tricky. It’s important to determine if you have the skills in-house or if you need to work with a consultant on your data migration project. Perform an honest assessment of your existing employees’ skills before you decide whether to tackle your data migration plan alone or with outside help.

 

Choose a data migration tool. While it’s possible to write your own code, there’s no reason to re-invent the wheel. There are numerous ETL applications available and using a commercial tool can shorten the timeline of your data migration project. ETL, or extract, transform and load, tools, can also help you address any differences in data formats as you transfer data from one system to another.

 

5. Execute your plan

 

Extract your data from the source systems, transform the data if necessary, and load it into the target system. If you need to take systems offline as you work, you may want to execute your plan over the weekend or during non-business hours to minimize impact to users.

 

6. Perform testing

 

Confirm that your data migration has been successful by testing the data on the new system. You’ll want to make sure that the data you have extracted, transformed and loaded has been extracted completely, transferred properly and loaded into the new system in the correct format. You’ll also want to test to determine if there are any issues with data quality, such as duplicate data or data loss.

 

7. Determine ongoing data migration needs

 

Data migration might not be a one and done type of situation. If you’re doing your migration in phases, repeat this process as often as you need to. Likewise, you may need to continue migrating data as part of an ongoing data integration initiative. Once you have your data migration process nailed down, it should get easier to execute.

 

Want to learn more about data migration?

 

Matillion Data Loader is a free SaaS-based data integration tool that seamlessly loads valuable business data into your cloud data warehouse. With a code-free, wizard-based pipeline builder to common data sources like Salesforce, Google Analytics, and more, Matillion Data Loader can help make your first data migration (and every one after) quick and easy. It’s also free. Sign up today to try Matillion Data Loader and kickstart your data migration project.

 

Matillion ETL software is cloud-native, purpose-built to support leading cloud data warehouse environments, including Snowflake, Amazon Redshift, Google BigQuery, Microsoft Azure Synapse and Delta Lake on Databricks.

See the power of Matillion for yourself. Request a demo to learn more about how you can unlock the potential of your data with Matillion’s cloud-based approach to data transformation.