Data is the new oil. Every day enterprises receive a lot of data from various internal and external sources. They use it for prescriptive, predictive, and cognitive data modeling that helps them to make informed, data-driven decisions. They use data warehouses to collect and manage data. Data warehousing has become so critical for businesses that according to Allied Research, its market size is expected to reach $51.28 billion by 2028.

For a long time, enterprises have been using Oracle’s Data Warehouse to manage data and gain valuable business insights. However, as data volume has increased, managing it on Oracle’s data warehouse has become tedious. There were also unstructured data coming in from different sources. This required more storage and processing, and it was hard for an on-premises data warehouse to manage it. It couldn’t be scaled up easily, and it turned out to be time-consuming and expensive.

Enterprises want warehouse solutions that perform advanced analytics, offer a real-time view on data, and need low data latency. That’s why they are shifting their data warehouse from on-premise to cloud-based data warehouse services such as Amazon Web Services (AWS).

However, migrating the Oracle data warehouse to AWS is not simple, especially when we are talking about the carefully collected data of customers.

So, here are some best practices to follow during migration.

Best Practices for Migrating Oracle Data Warehouse to AWS

Choose the migration strategy

The migration strategy you choose depends on various factors such as the size of the database, network bandwidth, whether the switchover will be done in one-time or over time.

There are mainly two strategies – one-step migration and two-step migration. One-step migration is used for small databases that are not mission-critical and can be shut down for 24 to 72 hours. In this period, the data is extracted from the source database, migrated to the destination database in AWS, and tested for consistency. Once validated, the database is switched over to AWS.

Two-step migration is apt for a database of any size but needs minimal downtime. So the migration is done in two phases. In the first step, the data is extracted from the source database during the non-peak time and migrated to avoid impacting operations. The database continues to run. In the second step, the changed data in the source database is propagated to the destination before switchover. The source and destination databases are synchronized. Once the changed data is validated, the database is switched over to AWS.

Choose the database

There are two main options available for running the Oracle data warehouse on AWS – RDS and EC2. Choose based on business needs.

Amazon RDS offers managed services to manage and maintain the database. It is easy to configure, can scale the database up to 64 TB, and replicates the Oracle database across different Amazon regions for better resiliency. However, there is a risk of lock-in as the codes and designs have to be specific to RDS. So, if the enterprise plans to move away from AWS in the future, it will have to redo the configuration. There is also the concern of 64 TB thresholds, so scalability is limited.

In Amazon EC2, enterprises get full control over setup, configuration, and maintenance. Amazon EC2 is more portable across other cloud service providers and scales up to 368 TB per database. However, as it is self-managed, it requires resources with higher technical skills who understand the technology well and manage it efficiently.

Choose the right tools for migration

Database migration involves two things – conversion of the schema and migration of the data. Enterprises use AWS Data Migration Service (DMS) and AWS Schema Conversion Tool (SCT) for both these steps.

AWS DMS helps with quick and secure migration to AWS even when the source database is fully operational. This reduces the downtime.

AWS DMS also helps in migrating data from commercial and open-source databases. AWS SCT is used to convert existing database schema from one engine to another.

Choose the data migration method

There are many migration methods used for migrating data from the Oracle database to AWS. These methods include – AWS Database Migration Service, Oracle SQL Developer Database copy, Oracle RMAN, etc. To choose the right migration method, enterprises must consider a few aspects such as:

• The size of the database
• Which database works with it
• Overall SLA
• Recovery Point Objective (RPO), i.e., how much data loss is acceptable after a data loss incident
• Recovery Time Objective (RTO), i.e., how much time does it take time to restore the process after the data loss incident.

Evaluate and map the business agreements with these methods to choose the right one.

Continue with the post-migration activities

Once the database is tested, validated, and the switchover to AWS is done, enterprises must focus on the post-migration activities. These activities could include:

• Shutting down the temporary AWS resources used during migration
• Reviewing the migration project documentation
• Gathering information such as the time taken to migrate, the manual vs. automated tools used for migration, and the total cost savings
• Closing the migration project and documenting the feedback and impact

Conclusion

Consumer demands are changing rapidly, and competition is getting intense. Enterprises have to use advanced data analytics to predict market trends and consumer needs and make data-driven decisions. Enterprises can leverage the simplicity, cost-effectiveness, scalability, and performance of cloud-based data warehousing to manage their humungous data volumes. Given how important data is, migration should be done carefully. Apart from following the above strategies, they must work with the right technology partner to ensure seamless and hassle-free migration.