What is data migration?

Data migration vs. data integration

Data migration is defined as transferring one or more datasets from one location or format to a target location or format. Data integration, on the other hand, consists of combining data from multiple sources with the goal of creating one unified, usable view of all data.

In simpler terms, data migration means moving data from one platform to another, while data integration means bringing data together.

Why businesses migrate

Data migration often occurs as part of a larger business optimization project. A data migration might take place in the following instances:

• The replacement of legacy systems with newer, more efficient solutions
• A data storage capacity expansion
• Moving data from on-premises data storage and management to a cloud environment
• The implementation of a new system to work with an existing system
• The consolidation of data structures due to a merger or acquisition
• Transferring data into a centralized database

What are the different types of data migrations?

There are multiple types of data migrations, and your migration project may involve one or more of these varieties.

Exports from customer relationship management (CRM) migration

CRM migration is when a business moves data from one business system to another. This type of migration occurs when a business chooses to either feed data into another system or use and manipulate data outside of the source system.

Examples include moving marketing event lists or sales spreadsheet data to the CRM or exporting data to create backups in other locations. These types of data migrations revolve around a company’s effort to consolidate information.

Storage migration

Storage migration happens when you move data from one storage location to another. This transfer occurs between physical storage devices with physical blocks of data.

An organization will often begin storage migration because it is upgrading its data storage equipment—not because it lacks data space. Storage migration encompasses different types of data movement, such as going from paper to digital or moving older, but still relevant, information from a CRM, where storage is at a premium, into a data repository.

Cloud migration

Cloud migration entails moving data from an on-premises data warehouse or data center to a cloud environment—or from one cloud-based location to another cloud-based destination. A cloud data migration usually involves a storage migration. Speed is a driving factor for cloud migration.

Database migration

When a new software solution is implemented, your IT teams need to transfer all of your data and information to that system—this is database migration. Database migration can mean moving from one business system to another or migrating teams off of spreadsheets and other disparate systems onto a more unified business system.

Database migration is one of the more frequently used types of data migration because most organizations consistently upgrade software to keep up with competitors.

However, issues can occur when the original data system operates in a different format and model from the new one. In this case, your team will need a data specialist to ensure proper database migration. 

Most businesses will upgrade their current database rather than the more difficult process of migrating to a new vendor. This is why some companies still choose to struggle with their original database systems, even if they are incapable of working optimally.

Business process migration

Business process migration usually takes place during mergers and acquisitions—though it can also occur when businesses want to enter new markets or need to meet new customer demands.

In each of these scenarios, organizations need to transfer the current data and information into a new system or environment, which is business process migration.

Validity DemandTools helps businesses maintain data integrity even while moving data into and out of Salesforce.

What are some data migration strategies?

If your organization needs to prepare for a data migration, the first step is determining which approach is right for your project. Your main priority is to ensure you’re choosing a data migration strategy that will run smoothly and maintain data integrity with minimal to no setbacks.

Below are two of the main data migration strategies.

Big bang migration

Big bang migration refers to an all-at-once approach—you initiate a complete migration of your data assets in one operation, in the smallest possible time frame.

When big bang data migration is underway, systems and platforms might be down and unavailable to customers, employees, and other users. It’s best to schedule a big bang migration overnight, during a legal holiday, or on a weekend when the data won’t be needed because of the likely and sometimes necessary downtime.

This type of migration allows companies to complete data migration quickly, which enables a faster turnaround. Users will not have to work with the original and new systems simultaneously while waiting for the data to transfer.

However, this approach does have some drawbacks, including higher costs and an increased risk of complication. As mentioned, while your systems are moving, your users may not have access to the database, which can hurt productivity if the organization is unable to schedule the migration during company downtime.

Smaller companies or those with small amounts of data have the most success with big bang migration.

Trickle migration

The trickle data migration approach breaks the data migration project down into sub-migrations. Instead of moving all of your data to the target system at once, the data migration occurs in different stages over a period of time ranging from a few months to a year.

Trickle data migration is also known as phased or iterative migration and it comes with competitive benefits. The biggest one is that it eliminates downtime. Since the old system and the new one are running during the migration, there is no downtime and employees and customers can access their data at all times.

Your company may choose two different ways to tackle trickle migration:

1. Data is migrated to the new environment and users get access to its new location: Your migration team tracks what information is moving to the new system and then makes sure that users are still able to access it. This can be complicated for your teams as they work to keep the two systems accurate and accessible.
2. Data is migrated to the new environment, but users don’t switch to the new system until the project is complete: This trickle migration approach works best for mid-to-large-size companies that work with large amounts of data. It’s also a great option for companies unable to afford any downtime for their users during data migration or companies that work irregular hours.

With the second approach, your team can choose to keep the original system operational throughout the entire data migration project. This way, users only have to switch to the new system once it’s completed. This can be a difficult task for your engineers, as data must be updated in real-time across both platforms. If any changes are made to the original system, they must also be applied to the new system.

Edmentum uses DemandTools to cleanly migrate thousands of records into Salesforce.

What does a good data migration process look like?

A good data migration process requires a well-thought-out data migration plan. Use the phases below to sidestep losses and delays.

Migration planning

This is the fundamental review stage before you migrate your data. It includes data analyses and data validation to determine exactly what you will migrate and where you will migrate it to. This includes knowing how much of your data actually needs to be migrated. Sometimes, there may be information that can be left behind—for example, if it’s inaccurate or incomplete, it shouldn’t be transferred to the new system.

This step helps your organization avoid wasting unnecessary time and money on your data migration. It can also flag any issues or concerns that might affect the transfer later on.

Auditing and profiling

This process requires a full examination and data cleansing of the data that you plan to move. Although time-consuming, auditing and profiling are essential to a successful migration.

At this stage, any possible conflicts or data quality issues, such as duplications or anomalies, can be identified and resolved. Most organizations will use automation tools to perform data deduplication.

This stage should also identify which data is related and how to ensure those relationships aren’t lost during the data migration.

Cleaning and deduplicating your data manually is time-consuming and prone to human error. When dealing with huge datasets, it’s better to use data management software to speed up the process and reduce the risk of mistakes.

Our data management tool, DemandTools, is a secure platform that helps you clean and maintain your CRM data efficiently.

Data backup

We highly recommend completing a data backup at this stage of your data migration. You can use your own internal backup process or one of the several data migration tools that have a backup feature.

Create a full backup of the data you’re planning to transfer, so you have extra protection against potential data loss during the migration.

Migration design

When approaching how to do data migration, your organization should:

• Detail migration and testing rules
• Create acceptance criteria
• Assign roles and responsibilities within your migration team
• Define timelines

There are freelance data migration specialists who can help you with these tasks or you can work with an ETL developer, data engineer, system analyst, or business analyst to create data migration scripts.

Migration execution

This phase covers the actual migration of your data to the new system. The time frame will depend on whether you choose the big bang or trickle approach and extend from a few days to multiple months.

Data migration testing

Although we’ve listed data migration testing separately, note that it should be performed throughout every phase of the migration to ensure success—from design and execution to post-migration.

Testing will ensure that your data quality remains high as it is extracted, transformed, and loaded into the new target system.

Post-migration audit

Complete a full audit of your migrated data, including a live test before allowing your users access. This will guarantee that the data was successfully transferred and logged. Once complete, you can retire your previous system.

Data migration risks

It is important to explore your options for data migration technology before putting your operations in the line of fire. Selecting well-rated technology from an authoritative source in the data migration industry is a proactive way to keep the following risks to a minimum.

1. Loss of data

Your organization requires a data migration tool that is well-tested and optimized for the types of data you use. This might include customer information, email lists, purchase histories, and marketing and sales data. Have a method for migrating data that lets you pull entries from sources without fear of errors that result in information being deleted before moving to a new system.

2. Compliance issues

Work with a professional in the data migration field to verify the information you will transfer from one outlet to another can be moved within compliance. Depending on the industry you work in, some data you store and handle may be subject to specific regulations. Sending information without the right approach can result in legal repercussions and fines.

3. Unwanted downtime

Your data migration process may require workers to stay out of systems until a transfer is 100 percent complete. Consider the types of data you will include in the migration process and when it would be appropriate to complete the job. Always leave room for flexibility during your data migration timeline should something not go according to plan. Times when workers will be away from their computers are optimal for completing data migration projects—consider public holidays, department trips, and employee vacations.

4. Corruption of data

Well-respected data migration tools get valuable information from point A to point B safely. The last thing you want is data scattered across different locations or for only some entries to make their way to a new system.

Data corruption can be a serious risk for businesses of any size—reducing the chances of error during the data migration process means finding a reliable partner with a long history of success. Find data migration tools made by a technology company with a track record of working with businesses you’ve heard of before.

5. Incompatibility

Once a data transfer is complete, you want the new system to be fully functional. Before starting your project, investigate the types of systems and data formats a data migration tool supports. This can save you from headaches down the road, such as information ending up in the incorrect location or entries being incomplete.

6. Data security breaches

Once a data transfer is complete, you want the new system to be fully functional. Before starting your project, investigate the types of systems and data formats a data migration tool supports. This can save you from headaches down the road, such as information ending up in the incorrect location or entries being incomplete.

7. Duplication of data

Once a data transfer is complete, you want the new system to be fully functional. Before starting your project, investigate the types of systems and data formats a data migration tool supports. This can save you from headaches down the road, such as information ending up in the incorrect location or entries being incomplete.

8. Slow data migration performance

The most dependable data migration tools enable your organization to transfer information from spreadsheets and software promptly. It’s wise to review a tool’s transfer speed capabilities to best plan ahead. Knowing whether your customer data will move to a new system within minutes, hours, or days is crucial for success. Eliminate unwanted delays with a data migration tool that supports the scope of your endeavors.

What to look for in a data migration tool

Data migration can be a complex endeavor, but following the tips in this article will help you put together a solid data migration plan that helps you migrate data effortlessly.

Data migration planning is only the first step. Executing it is the second. There are various data migration tools that will make the process easier. When comparing these data migration tools, it’s important to choose one that offers the following:

• Reliability: Based on reviews, does the tool perform reliably?
• Scalability: Are there any data limits that could cause issues if you want to migrate a larger amount of data in the future?
• Flexibility: How easily can you customize the tool’s settings to your needs?
• Security: Does the tool have data security features? Does it uphold the same security requirements as your company?
• Speed: How quickly does data processing happen?
• Pricing: Does the tool fit your budget?

Additionally, your business’s data migration solution should help manage the quality of your data during the migration process through duplicate identification and merging, standardization, record ownership management, and the ability to understand where data may overlap between systems.

Each of these considerations will help you maintain high-quality data. For example, during data migration, Leads may be created as Contacts in the system that you’re moving from with a particular type to denote whether it’s a customer or prospect. With the right tool, this information will be migrated over to the Lead object in the new system.

Operational tools that fulfill all of these requirements are key to successful data migration. Thanks to Validity® DemandTools®, you can manage your organization’s Salesforce data quickly and accurately. There’s a reason why thousands of businesses count on our technology for CRM efficiency—we migrate data in minutes instead of weeks or months. Cleanse and manage Salesforce information to work both efficiently and profitably.