Data migration
What is data migration?
Data migration describes a planned transfer of data from existing systems into new SAP target systems, such as SAP S/4HANA. The process includes master data, transaction data, and historical data, all of which is transferred consistently, completely, and correctly.
How does data migration work?
The data is analyzed, cleansed, transformed, and finally loaded into the target system. This process usually consists of multiple test and migration runs, to ensure data quality, system stability, and functioning business processes before going live.
What are the advantages of data migration?
- Seamless transition to SAP S/4HANA
- High data quality from the outset
- Minimization of operating risks during the go-live
- Faster acceptance by users
- Foundation for efficient processes and analytics
What are the disadvantages of data migration?
- Large effort required for planning and coordination – the devil is in the details
- Dependence on the quality of data in the legacy system
- Time-consuming and resource-intensive test phases
What are the essentials of data migration?
- Early data analysis and data cleansing
- Clear definition of which data will be migrated
- Close collaboration between business units and the IT department
- Realistic time planning for tests and validation
What is the difference between data migration and data cleansing?
A system switchover gives you the unique opportunity to get rid of obsolete, incomplete, or low-quality data by cleaning up or even deleting it in the current systems prior to migration. This cleanup prior to the data transfer is called “data cleansing”.
The actual migration is then the subsequent data transfer to the new system. That means data cleansing is the step that should precede data migration, because it can significantly simplify and speed up the migration process. And getting rid of relics from the legacy systems will make it easier to get started in the new application as well.
Is data migration recommended?
Yes. Every system changeover – in particular to SAP S/4HANA – requires a structured data migration, to reduce risks and safeguard business operations.
What is the right way to use data migration?
Successful data migration starts early on in the project, follows a clear methodology, and is tested multiple times. The decisive factor is to treat migration as a business topic, not a technical task.
In addition, the data migration must go hand in hand with the design of processes and solutions, to acknowledge process changes compared to the legacy system in the form of appropriate mapping and migration rules.
Is a separate data migration recommended for system changeovers?
A changeover is essential in SAP transformations, system consolidations, and carve-outs. Professional data migration will speed up the transition and lower subsequent costs.
How does data migration help in everyday business?
After going live, businesses benefit from robust processes, reliable results, and high user acceptance. Managers immediately receive resilient data, while employees can work without constraints.
Who can support me with data migration?
Successful data migration requires functional and technical expertise – gicom offers both.
What tips can you provide for data migration?
- Data migration is one of the most critical success factors in SAP transformations. An early start reduces project-related risks and prevents delays shortly before going live.
- Which data to migrate is a business decision. Specialist departments – not just the IT department – need to define which data is relevant, up to date, and necessary.
- “Garbage in, garbage out” is especially true of migration projects. Data cleansing, harmonization, and duplicate check should be performed before the first migration test.
- Not all historical data needs to be migrated. Targeted selection will reduce complexity, costs, and runtimes – without any loss of information.
- Migration is an iterative process. Running multiple test migrations will improve data quality and performance and engender trust among users.
- Technically correct doesn’t automatically mean functionally correct. Specialist departments must actively review and approve migrated data.