Data migration: what is it and how do you approach it successfully?

Do you want to switch to a new system? Want to upgrade your system to the latest technologies? Or is a merger or acquisition coming? Then you will have to deal with a data migration.

Data migration involves moving data from one system to another. It is important to ensure that the integrity, consistency and security of the data continue to exist. Successful data migration requires careful planning, execution, and verification. This way, business activities can continue to run undisturbed.

What is data migration?

The meaning of data migration is the process of transferring or moving data from one storage system or format to another. All while maintaining the consistency and usability of the data. For example, consider moving data from an older database to a new one, migrating from local data storage to the cloud, or bringing data from different sources together into one unified platform.

When do you do a data migration?

There are several reasons why you do data migration. If you want to modernize your IT infrastructure, implement new systems or if you want to optimize your business operations by streamlining data-driven processes. We often see companies dealing with data migration when there are mergers or acquisitions, a need for better data security or regulatory compliance.

How do you perform a successful data migration?

Are you going to do a data migration? Then it is important that this process is done carefully. This step-by-step plan can help you ensure that you do not forget or skip important parts.

  1. Planning | Set clear objectives and timelines for the migration. Gather all stakeholders involved and assemble a project team.
  2. Data Profiling | Analyze and understand existing data sources and the quality, structure and complexity of your data.
  3. Data Cleansing | Filter and normalize the data to remove inconsistencies and duplicates. This ensures higher accuracy.
  4. Selection of tools and technologies | Choose the right tools and technologies that match the nature and scope of the migration. For example, ETL (Extract, Transform, Load) tools and automated migration tools.
  5. Testing and validation | Conduct extensive testing to check the integrity, consistency and usability of the migrated data. By comparing source and target data, doing performance testing and user testing.
  6. Implementation and monitoring | Deploy the migrated data into the new system and continuously monitor performance to resolve issues quickly.

Example data migration plan

A.S.F. Fischer wanted to centralize her product data. This way they could automatically manage and distribute all information from a central application to other systems. Think of Unit4 Multivers Extended and the 2BA platform. The demands? A web application where A.S.F. Fischer has the freedom to expand this in the future with functionalities that are separate from the P.I.M. system. SIENN offered a solution that allowed A.S.F. Fischer was provided with a modern web application that met the requirements of speed, flexibility and scalability, with a total offering of approximately 30,000 different articles and gigabytes of product media. The openness of the platform offers the opportunity to accommodate much more functionality. Read the whole story here.

For example, the data migration plan based on the case of A.S.F. Fischer look like:
Data Migration Plan for Centralization of Product Data

  1. Objectives
    The purpose of this data migration is to transfer all product data from A.S.F. Fischer in a web application, which can then be integrated with other systems such as Unit4 Multivers Extended and the 2BA platform. Make sure that the web application is flexible, scalable and future-proof, and that it can be expanded with new functionalities that are separate from the P.I.M. system.
  2. Project team
    The project team consists of a project leader, IT architect, developers, database administrator and representatives from A.S.F. Fischer (e.g. the IT manager and product manager)
  3. Planning and content of different phases
  • Preparation and analysis
    • Analyze current systems and data structures to create an inventory of all product data and associated media.
    • Identify the requirements for the new web application, including flexibility, scalability and future expandability.
  • Data cleaning and preparation
    • Clean and normalize product data to resolve inconsistencies and duplicates.
    • Establish a mapping between the existing data structures and the new web application to ensure a smooth transition.
  • Development of the web application
    • Develop the web application using the BizzLayer platform, DataSync and the P.I.M. module to meet the requirements of speed, flexibility and scalability.
    • Implement functionalities such as management of product data, media, and the possibility of expansion with new functionalities.
  • Integration with Unit4 Multivers Extended and the 2BA platform
    • Integrate the web application with Unit4 Multivers Extended and the 2BA platform to enable seamless data exchange.
    • Ensure data consistency and integrity are maintained during integration.
  • Testing and validation
    • Perform extensive testing to ensure that the web application works correctly and meets all requirements.
    • Validate data integrity and consistency after migration.
  • Execution of the migration
    • Execute the migration according to the predefined schedule and timelines.
    • Monitor migration progress and resolve any issues or errors immediately.
  • Aftercare and follow-up
    • After migration, verify the accuracy of the migrated data.
    • Provides training and support to users of the new web application.
    • Document all steps and findings for future reference.

What problems often occur during a data migration?

All kinds of different problems can arise during a data migration. From technical challenges to organizational and operational complications. These are some examples of common problems:

  • Data loss and corruption. Especially during large-scale migrations or when there are complex data structures.
  • Incompatibility between systems. Because old and new systems may have different data structures, formats and validation rules.
  • Missing or incomplete data. Sometimes not all necessary data is migrated properly due to missing or incomplete information in the source systems.
  • Downtime and disruption to business operations. If the data migration is not properly planned and executed.
  • Performance problems. Such as delayed system response or longer loading times due to inefficient data transformations or insufficiently optimized database infrastructure.
  • Lack of user acceptance. If the new systems do not meet user expectations or if insufficient training and support is provided.
  • Security risks. Have too few security measures been taken? Then data is vulnerable to unauthorized access, data theft or privacy breaches during the migration process.
  • Cost overruns and delays. Due to unforeseen complications such as technical problems.

Need help with a data migration?

You read it: for a successful data migration you need expertise and experience in data management and system integration. Are you looking for such an expert? Then SIENN can help you with your data migration project. Our team of experts will help you at every stage of the migration process. From planning and analysis to implementation and validation. Please feel free to contact us for more information.