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Best Practices to Avoid PLM Data Migration Nightmares

Data migration is a complex process. It involves making a copy of an organization’s current data from one device to another device without disrupting the business operations, and finally redirecting all activity to the new device.

Data migration is a complex process. It involves making a copy of an organization’s current data from one device to another device without disrupting the business operations, and finally redirecting all activity to the new device.

Why do organization migrate data? What are the business drivers?

If your organization is planning on migrating, you are not alone.  I am regularly asked, “Why do organizations migrate data?”  Some of the reasons organizations tend to migrate from legacy solutions are:

  • When they procure a new hardware or software
  • When they want to optimize the storage
  • When they want to relocate their data centers
  • When merger and acquisition occur
  • When it is part of the DR strategy

Have you ever wondered why many data migration projects fail?

Most IT managers consider data migration a routine exercise and pay little attention to it. Data migration failures also happen due to the absence of effective data quality management across the project and lack of planning and prioritization. Given the value of your data, data migration requires specific skills, tools, and plans.

Best practices to minimize or avoid data migrations PLM project failures

To minimize the business impacts of data migration failure, organizations need to deploy a consistent, and repeatable methodology that incorporates planning, technology implementation and validation.

  • Planning a migration strategy Planning is critical to the migration process and depends on its size and scope. You need to identify the requirements, both hardware and software, outlining the stakeholders and their roles and ensure they work together to align objectives and timelines. Moreover, the current and future development plan need to be built in and documented.
  • Technology – Identify and implement a simple migration technology that is easy to use and can easily be adopted by analysts and users. ETL technology is preferred by users for its unique ability to handle the extreme requirements of data migration. However, the ETL tools license cost is high.
  • Data validation – Poor data quality can create problems. You need to extract, clean and transform data before setting it up for migration. The quality of data is improved as you can identify omissions, errors, or issues. Moreover, it is important to determine what data to pull forward, what to do with rest of the data, and how to map and enhance data for the target application needs.
  • Legacy data – Source applications, servers, or databases that are not required at present, need to be archived and be a part of the migration process. Archive it in a way that it can be accessed fast.
  • Data Movement – Segment the migration process to run it more efficiently. You can audit, map, test and transfer data in staggered phases. You can stick to budgets, timelines, and deliver better results without disrupting other processes.
  • Testing – Testing and validating the migrated data, ensures its integrity, accuracy, and the formatting. The ultimate test is the user acceptance testing.

Unlike those required for other IT projects, data migration approach has to be systematic and holistic. We at PROLIM understand the challenges in making a data migration project successful. With our data migration platform Diaspora and proven data migration best practices, we make the overall process consistent, faster migration and cost effective. Need assistance with planning and suggesting right PLM Data Migration approach, PROLIM is your go to partner.

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