Major Data Migration Mistakes and How Best to Avoid Them

Technology is changing rapidly in today’s fast-paced business marketplace. To keep pace with these advancements and disruptive innovations, organizations need to continuously invest in data migration and new technology platforms, to stay current. Data migration is one of the biggest challenges, as it is complex and very risky.

Usually, Data Migration involves multiple steps in the Extract-Transform-Load (ETL) process. It means extraction of data from the old system or source and then load data into the new systems based on data mapping and transformation guidelines.

When it comes to migrating all of your business’ data there are so many mistakes that you are likely to make that you should be aware of and learn how to avoid them.

Common mistakes and challenges in data migration projects include:

  1. Not involving business users –The most common mistake made by an organization during the planning and implementation phase is, failing to assign the right people to the key roles.  Most of the time, it is assumed that data migration is an IT problem. But there are other users, across the organization who are also affected by it. Therefore apart from IT, experts, and data users also need to be involved in the migration process.
  2. Inconsistency and poor quality legacy data – Companies want to migrate data from legacy systems and PDM/PLM systems to a new PLM system. But these legacy systems can have a lot of information that may not be relevant or not structured properly. You need to assess your legacy data to determine what best is to be migrated to the new system.
  3. Issues integrating product data throughout the product lifecycle – Lack of proper planning and an intelligent approach for migration of PDM and PLM data is one of the most common mistakes that can lead to data migration failure. From conception, design, manufacture, operation and transference, a proper migration strategy is required to meet the integration challenge encountered in PLM execution.
  4. Wrong data migration tools – With a number of data migration tools available in the market, it is important to identify the right tool that can meet your data migration requirements. For instance, a data migration strategy such as the Diaspora 2.0 from PROLIM is one of the best tools that can lead to ease and accuracy in data migration.
  5. Failure to test and validate the data migration process – Companies often don’t spend enough time to align the data testing, validation, and migration process to the project timeline. There is a general tendency to test and validate the process once it is completed. But validation and testing need to be an ongoing process, built into the project lifecycle to help identify defects early and save cost.

Conclusion 

With changing technologies, the problem of migration will continue to grow. To deal with this effectively, a well-executed PLM data migration strategy is required that can bring in significant business benefits. PROLIM’s data migration tool works with any legacy system you have or any new PLM system that your company wants to implement.

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