Get a list of best practices on how to migrate your data for SAP in 2025 and beyond.

SAP Data Migration: Best Practices 2025

Data migration is the process of transferring data from one source to another. Speaking about SAP data migration in particular, the end destination of your data is an SAP ecosystem, while the original source may be either SAP or non-SAP.

SAP data migration encompasses data cleansing, validation, profiling, QA, conversion, and other procedures. The latter — Data conversion — is executed through the ETL (Extract, Transform, and Load) process.

SAP data migration is not an easy task. To help you successfully accomplish it, we prepared a quick guide on data migration best practices to help you successfully migrate your data to SAP environments, paving the way for digital transformation.

When Do You Need Data Migration?

The necessity for data migration comes from various reasons and factors. While this procedure is not something you do on a regular basis, you may need it after important, enterprise-level updates, like hardware renovations, implementation of a new system, changes in business processes, or overall company growth, where current data storages may no longer be sufficient or/and hinder further expansions.

SAP is the environment that contributes to digital transformation and sustainable growth, ensuring smooth functionality and efficiency as your business expands and your IT operations become more complex. Add to this, all your data being stored within a single SAP system, allows you to use accumulated information for data-driven decisions. All of these make SAP a choice for many businesses who are in search of an all-encompassing data management solution.

Businesses that have been using SAP for a long time may also need SAP data migration to, say, migrate data from SAP ECC to SAP S/4HANA, which is the newest and the most functional ERP solution. And since SAP will stop supporting SAP ECC in 2027, SAP S/4HANA migration becomes a necessity for these businesses.

Types of Data Migration

Data migration types vary depending on the type of data transferred, the goal of the migration process, and/or the environment (infrastructure, tools, processes, etc.) where data migration is taking place. Let’s take a closer look at the types of data migration.

Storage migration

Storage migration is the process of transferring data from an existing, legacy storage or several fragmented storages to a more up-to-date and, most often, unified one. Storage data migration helps organizations unify data for better decision-making and strategic planning to improve performance and cut costs on connecting and maintaining multiple data storages.

Database migration

Database migration implies moving data to a new database that better fits the changing needs of a growing business. The choice of database solutions is big, so businesses can choose from different options depending on their specific needs. Most often, businesses migrate from typical on-prem databases to a NoSQL database, an SQL database in the cloud, or even a DaaS (database-as-a-service) solution.

Application migration

Application migration takes place when an enterprise has to change application vendors or upgrade the current system to obtain the functionality that would meet the needs of a growing business. Application migration includes multiple data transformations, such as data model, schemas, and API changes.

Cloud migration

Cloud migration is the process of shifting from on-premise to the cloud. Companies often do this for more scalability, as well as storage and cost optimization. One of the examples of cloud data migration is moving from SAP ECC to SAP S/4 HANA Cloud within the GROW with SAP (for small- and medium-sized businesses) or RISE with SAP (for large enterprises) digital transformation offerings.

Business process migration

Business process migration includes the transition of databases and apps that hold customer, product, and operation data. This type of data migration usually happens after a business acquisition, merger, or reorganization, as these events are often followed by changing data systems or applications.

Hybrid migration

Hybrid data migration is a process that combines on-premise and cloud migration options. Businesses use this method if they need to keep some data management processes on-premise while moving all the rest to the cloud or vice versa.

SAP Data Migration Best Practices

In order to execute SAP data migration successfully and minimize all the associated risks, an enterprise has to follow the established best practices. Here’s the list of the top data migration advice for 2025:

Devote time on planning and preparation

Thoroughly define the scope of the data to migrate, set your data migration goals, create a migration strategy, and make sure to follow data governance policies. Doing this at the very first stage will help you avoid disruptions and migration lags in the process.

Involve key stakeholders

Let the business users themselves participate in the data migration process. This will help you save time on their consecutive training, as they’ll be aware of the new system peculiarities right from the start and will have more time to adjust.

Run test migrations

Test the required migration scenario several times before you start an actual data transfer process. This will help you identify vulnerabilities and fix them in a timely manner, as well as come up with a backup plan in case something goes wrong during the process. Data migration platforms such as DataLark can help you here, where you can easily visualize the data migration process and make sure you correctly connect sources and targets before starting the migration.

Ensure minimal downtime

Thanks to test migrations, you can fix all possible migration issues in time, and hence fine-tune the performance of your data migration scenario before starting the migration process. This is especially important when migrating dynamic data (e.g., transactional) with minimal lags and process downtime.

Perform data validation

Validate your data after the migration is complete. This way, you’ll be able to ensure that the new SAP system works as expected, and your data has been transferred safely. It’s recommended to use dedicated SAP tools for data validation, as they can easily let you identify inaccurate, inconsistent, incomplete, or missing data. Plus, the results are presented in a user-friendly graphical format.

Provide post-migration support and monitoring

Keep monitoring your data after the migration is complete. Ongoing monitoring is the best way to identify any possible problems and come up with timely adjustments to keep your new data environment functioning efficiently and allowing for further business scalability and growth.

SAP Data Migration Challenges

SAP data migration is a complicated process that requires thorough preparation, and there are several challenges that can stand in the way of a business’s successful migration. Especially if the enterprise is big, old, and has a lot of legacy processes that aren’t automated enough or not automated at all. Here’s the list of the most common SAP data migration challenges and the ways to overcome them.

Data quality issues

Insufficient data quality monitoring can result in numerous errors and inconsistencies, which, consequently, affects the quality of the migrated data and the functionality of the entire SAP system where this data is migrated. To handle data quality issues in advance, an organization needs to pay strict attention to data cleaning, validation, and mapping not only before the migration but on an ongoing basis.

Large data volumes

Large enterprises often face the challenge with large sets of data (usually fairly unorganized and inaccurate) that are hard to move to a new system without taking time and resources on its convenient organization. To avoid extra costs and business lags related to this, organizations should think about prioritizing critical data and consider a phased data migration approach to reduce system load. Solutions with SAP ETL functionality will also help, as they allow speeding up the process and systematizing the data.

Integration and compatibility issues

Integration and compatibility challenges are common for businesses that migrate data from diverse legacy systems with different data formats. SAP data integration platforms and services can help here, as they allow enterprises to prepare their data for proper functioning in a new SP environment.

Consequences of Poor Data Migration

If SAP data migration goes wrong, the consequences can be a disaster. Missing data, report errors, inaccurate analytics, or system bugs will most likely result in lost time and money. Here’s the last of what to avoid and why to stick to the data migration best practices above:

• Data loss. Losing your crucial data as a result of poor data migration may lead to lost clients, lower productivity, and business lags because you’ll need additional time and money on data recovery.
• Operational disruptions. Data loss combined with system disruptions can stop business operations, which can result in productivity lags and revenue loss. In industries like healthcare or pharmaceuticals, operational disruptions may lead to even more serious problems than just money losses.
• Security and compliance risks. Data inaccuracies can lead to non-compliance with regulations such as GDPR and HIPAA compliance. This is a direct path to legal penalties and associated financial losses.
• Reputational damage. Poor data migration may result in data leaks. If this leads to customers’ sensitive information disclosure, you can face serious reputational damage. Clients will start trusting you less, change vendors, or even create legal problems.
• Financial losses. Failed migration can be fixed, but the price is going to be very big, to say nothing about lost clients and additional expenses to recover from business disruptions.

How DataLark Overcomes Common SAP Data Migration Challenges

When examining the core challenges in data migration, it's important to consider how a comprehensive methodology addresses these issues in real-world scenarios. Based on our extensive experience with enterprise data management, the DataLark approach offers distinct advantages in tackling the most pressing migration obstacles.

Challenge: data quality issues

Case study: manufacturing conglomerate transformation

A global manufacturing enterprise with operations in 17 countries faced critical challenges when migrating their 15-year-old SAP ECC system to S/4HANA. Their master data was inconsistent by approximately 22% across material, customer, and vendor records, threatening to compromise the entire migration process.

Problem: The company's previous migration attempts resulted in incomplete data transfers and system interruptions, costing them more than 500K USD in operational delays and remediation efforts.

Solution: DataLark's integrated approach addressed this challenge through:

• Implementing comprehensive data profiling that identified 87% of inconsistencies in the first assessment phase
• Deploying specialized cleansing algorithms that reduced duplicate entries by 94%
• Establishing governance protocols that prevented new inconsistencies during the migration process

Result: The enterprise completed their migration with 99.7% data accuracy, eliminating post-migration data quality issues that would have required manual intervention. This resulted in approximately 3,800 person-hours saved in post-migration data correction activities.

The key difference in our methodology lies in the seamless integration between the assessment, profiling, and cleansing stages (Steps 1-2 in our process). Unlike automated "black box" solutions that apply generic rules, DataLark's expert-guided profiling adapts to the specific data characteristics of each organization.

Challenge: large data volumes

Case study: financial services provider transition

A mid-size financial services provider with over 10TB of transactional data needed to migrate to S/4HANA while maintaining continuous operations for their 1.4 million customers. Their critical concern was minimizing downtime while ensuring complete data availability.

Problem: Their initial estimates using conventional migration tools suggested a minimum 72-hour downtime window, which would have resulted in approximately $2.3 million in transaction processing delays.

Solution: DataLark's methodology addressed this challenge through:

• Implementing a phased migration strategy that prioritized critical transactional data
• Utilizing intelligent staging environments that pre-processed transformation rules
• Deploying parallel processing protocols that reduced data transfer time by 78%
• Leveraging incremental synchronization to maintain data consistency during extended migration periods

Result: The organization completed their core data migration with only 8 hours of downtime, representing an 89% reduction from traditional approaches. Post-migration analysis confirmed 100% data integrity with zero transactional discrepancies.

The critical difference in our approach is the integration between the data staging, controlled migration, and incremental synchronization capabilities (Steps 3-4 in our process). This integration allows for strategic prioritization of data elements based on business criticality rather than technical considerations alone.

Our experience has consistently demonstrated that addressing migration challenges requires more than technical tools—it demands a methodology that balances technical precision with business context understanding. The DataLark approach represents this balance, offering a framework that consistently delivers successful outcomes for complex SAP migration initiatives.

The DataLark Approach to SAP Data Migration

While following the general best practices is essential, implementing a structured methodology is equally important for successful data migration. DataLark has developed a comprehensive 5-step approach that transforms traditional migration challenges into strategic advantages. This methodology specifically addresses the complexities of SAP environments while maintaining the flexibility that many "out-of-the-box" solutions lack.

5 key steps of personalized data migration: the DataLark approach

Advantages of DataLark's Personalized Approach

DataLark is a comprehensive service developed with the understanding that each SAP infrastructure is as unique as a fingerprint.

You know what the main problem is with most "out-of-the-box" migration solutions? They assume all business processes are the same. It's like trying to fit a one-size-fits-all suit on people of different builds. Some might get lucky, but most will struggle.

DataLark takes an entirely different approach. Our clients often say: "Finally, someone who truly understands our specific needs!" And it's no surprise—personal attention to detail is in our DNA.

Expert control instead of a "black box"

When AI algorithms make decisions for you during migration, you effectively lose control. It sounds progressive, but what happens when something goes wrong? You're left alone with a "black box."

With DataLark, every decision is made by experts who understand not just the technical aspects but the business context of your data. It's like the difference between autopilot and an experienced pilot—both can handle standard situations, but in unusual circumstances, only human experience and intuition can find the optimal solution.

Flexibility unavailable in "boxed" solutions

Imagine realizing mid-migration that you need additional data transformation or changes to field mapping logic. With traditional solutions, this means stopping the process, reconfiguring, and losing time.

DataLark allows you to adapt the process "on the fly." Our clients value the ability to make changes at any moment without halting migration. It's like the difference between a train that can only move on tracks and an off-road vehicle capable of changing routes at your discretion.

Transparency that builds trust

With DataLark, you always know exactly what's happening with your data. Our detailed reporting doesn't just inform you about results—it provides a complete understanding of each stage of the process and justification for every decision made.

In a world where data management is becoming critical for business, such transparency is invaluable. This isn't just migration—it's building the foundation for your company's future growth.

Our approach is particularly effective for enterprises that value an individualized approach and understand that quality data migration is an investment in the future, not an expense item.

Bottom Line

SAP data migration is a complicated process that requires thorough preparation and careful planning. With this guide on data migration best practices, professional assistance, and proper SAP data migration solutions like DataLark, data migration is more likely to go smoothly, and your data will be transferred to a new system safely.