Step-by-Step Guide on Migrating Data from Oracle

o you need to migrate data from Oracle to another platform? The data migration process might seem daunting, but following the right steps can ensure a seamless and frictionless migration. In this blog, we’ll provide you with a step-by-step process for migrating data from Oracle, along with some general information about data migration.
Last updated
September 14, 2023
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Do you need to migrate data from Oracle to another platform? The data migration process might seem daunting, but following the right steps can ensure a seamless and frictionless migration. In this blog, we’ll provide you with a step-by-step process for migrating data from Oracle, along with some general information about data migration. Read on to make sure Oracle data migration is successful!

A Brief Overview

Today’s data-driven business ecosystem is certainly a net benefit for businesses. Big data gives businesses the ability to analyze their operations, their consumer needs, and much more. These reports and analytics allow businesses to be more efficient and increase revenue. Of course, this means that businesses also need to embrace data management tools to make the process of using data easier. That’s where tools like Oracle can be helpful. However, it doesn’t mean that every feature on the Oracle platform is straightforward and easy to understand. With that being said, let’s talk about some of the basics of data migration.

What Is Oracle?

First, let’s talk about the Oracle platform. Oracle is a relational database management system, which essentially means a database that collects and stores data that is defined by type and relationships. Oracle offers a stack of cloud applications and cloud platform services to help organizations create, manage, and access their data.

Oracle is developed by Oracle Corporation, which is one of the largest software companies in the world. Oracle software tools are used by numerous industries in various departments, such as supply chain management, financial management, human resources, data management, and more. Oracle’s scalable architecture can handle large amounts of data, making it a popular choice for many companies.

What Is Data Migration?

In its simplest definition, data migration is the process of moving data from one system to another. This could mean moving data to databases, applications, or even from one format to another.

Data migration is a critical business process, allowing businesses to upgrade to new systems and technologies, centralize their current data infrastructure, change their data model, and more. Regardless of why an organization needs to migrate data, it’s important that the data is transferred as consistently and securely as possible.

Data migration can be a complex process, but careful planning and execution can ensure success.

Why Is It Important?

Data migration serves several important functions, but it typically boils down to improving and upgrading an organization’s current data systems. Here are some of the reasons a business might initiate a data migration:

  • Upgrades for current or legacy systems - As mentioned, data migration allows organizations to replace or upgrade outdated systems.
  • Moving to the Cloud - Data migration allows businesses to move their data to the cloud
  • Data Consolidation - Organizations that want can consolidate and centralize data can do so through data migration

Data migration is essential as technology and data management continue to evolve. That’s why it’s important to understand the process and how to implement a migration.

What Are the Different Types?

There are various different types of data migration. The type you use will depend on the places you’re moving data between. Here are the types of data migrations:

  • Storage Migration - Storage migration is the process of moving data from one storage location to another. You may use a storage migration if you’re upgrading or consolidating storage devices. Storage migration is usually done to keep up with the latest developments in storage technology.
  • Application Migration - Application migration is the process of moving data from one application software to another. This is usually more involved than a storage migration since it may require changes to infrastructure and data formats due to the environment of the new application.
  • Database Migration - Database migration involves transferring data from one data management system to a new one or transferring to the updated version of your current DBMS. This process often involves data transformation to adhere to the new database.
  • Data Center Migration - A data center migration involves moving a physical data center to another location. It may also mean moving a physical data center to the cloud.
  • Cloud Migration - A cloud migration involves moving data from on-premises storage to the cloud. This is something that many organizations are doing to have more efficient access to data while also adding flexibility and scalability to their data processes.
  • Business Process Migration - Business process migration is typically needed for business mergers or acquisitions. It involves migrating processes, data, governance, and more with the acquiring company.

Understanding the different types of data migration methods available can help organizations choose the best approach for their specific needs and ensure a smooth and successful migration process.

Steps To Follow When Migrating Data

Data migration is a complex process with a simple definition. While data migration simply means moving data from one system to another, the steps to do so can be complicated. Careful planning is needed to prevent data loss, corruption, or security issues. To ensure a smooth migration, follow these steps for pre-migration, migrating, and post-migration.

What To Do Pre-Migration

Before you start the data migration process, it's important to take certain steps to ensure the process goes as smoothly as possible. Here are some important things to consider before you begin:

  • Plan your migration strategy - Plan your strategy thoroughly and carefully. Set out a data migration timeline and schedule and decide on your data migration method (which we’ll touch on next). Assess your data source and see how much data will be pulled over. Being thorough in your strategizing can help prevent problems down the line. You should also make sure to outline personnel responsibilities and bring on any specialists you may need for the task.
  • Conduct an audit - Once you have your strategy outline, audit your data to see if it’s accurate and reliable. Check for anomalies, duplications, and other issues that could hinder the migration process. You may need to cleanse data before moving on to your migration, depending on what you uncover.
  • Back up your data - Ideally, your data migration is a success. However, things can happen, and you want to have a copy of your data to fall back on in the event of any issues. Make sure to store your backup in a safe and secure location before moving on to the migration process.
  • Test your environment - Conducting tests will help ensure your migration build can handle implementation.

By following these pre-migration steps, you'll be better prepared to tackle the data migration process with confidence and achieve a successful outcome.

Choose Your Method

One of the most important steps in your pre-migration checklist is deciding what migration approach you want to take. There are two common methods, which have their own set of advantages and disadvantages. Which one you use will depend on factors like the size of your organization, your capacity for downtime, and the data you’re migrating. Let’s take a look at these two approaches:

  • Big Bang Data Migration - The idea behind the big bang approach is to move all of your data in one set event. This option can be attractive because it is quick, simple, and cost-effective. However, it also means that your systems will be down while the migration takes place. 

Big bang migrations require careful timing, so operations are affected as little as possible. This can also be an expensive method, as the network and organization resources may not have the throughput to handle such a large migration, which causes further delays and expenses.

Generally, the big bang approach is best for smaller organizations or organizations that don’t need real-time data as part of their regular operations.

  • Trickle Data Migration Approach - Trickle data migration, as you might expect, is a phased migration. Rather than moving all of your data all at once, the migration process happens in smaller sub-migrations. Each sub-migration is treated as its own migration, which can help mitigate risk and loss of data quality.

The other advantage is that the old system can continue to run as the migration takes place, causing little to no downtime for users and stakeholders. Of course, the downside means that the process is much more complex and time-intensive. 

Generally, the trick data approach is best for large organizations with a lot of data or organizations that can’t spare any downtime.

Ultimately, the method you choose will depend on your specific needs and requirements. It's important to carefully evaluate your options and choose the method that is best suited for your migration project

Migrating Data From Oracle

Now that you have your strategy in place, your data backed up, and your approach is chosen, you’re ready to implement your data migration.

As outlined in your strategy, there should be processes in place for monitoring the migration process as it happens. You should also have plans in place to address unexpected errors if they occur.

To start your migration, connect to your target database. Use your chosen approach and migration tools if needed to implement the migration. Eventually, the migration process will be complete, and you’ll be ready to move on to your post-migration checklist.

What To Do Post-Migration

Once your data migration from Oracle is complete, there are a few things you need to do to ensure that your data is properly functioning in its new environment. Here are some important steps to follow post-migration:

  • Conduct an audit - Once the migration is complete, it’s important to make sure the data maintains its integrity. Conduct an audit to ensure the data is accurate and address any discrepancies or errors.
  •  Check system functionality - Ensure the new system is working as expected.
  • Retire the Old System - You will eventually want to decommission the old system, but only do so once you’ve verified the data is accurate and you’ve ensured the new system is functioning properly
  • Monitor Performance - It's important to monitor the new system's performance regularly. Look out for any performance issues and resolve them immediately.

By following these post-migration steps, you can ensure a smooth transition to a new environment with accurate data and minimal system issues. Remember, data migration is an ongoing process, so it's essential to continually monitor the system's performance and maintain the accuracy of the migrated data.

Best Practices For Successful Data Migration

To wrap up, here are some general best practices for successfully migrating data:

  • Plan ahead - Always create a comprehensive strategy for migration and plan ahead.
  • Cleanse data - Audit and cleanse data if needed before making the migration. It’s easier to fix errors and inaccuracies pre-migration, so the new system has a clean start.
  • Backup data - Backup all data that is being migrated in case something goes wrong.
  • Test your migration strategy - Test your migration approach before full implementation 
  • Create your migration team -  Putting together a dedicated team for the migration process will ensure all your bases are covered.
  • Don’t shut the old system off yet - Leave the old system running until you can verify that the migration was successful.

Try Secoda for Free

Organizations that want to centralize their data and enable self-service analytics should consider a data management tool like Secoda. Secoda makes it easy to combine your data catalog, data lineage, data discovery, and more on one platform. With Secoda, you can empower your team to make the most of your data. Ready to learn more? Schedule your demo or try Secoda for free today.

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