It’s vital that you have a solid data migration plan if your company is going to be implementing a major data migration project. In most cases, organizations are dealing with a great deal of inconsistent data before they migrate to a new system, including missing or inaccurate data. The quality of your data is crucial in this day and age, and there’s no sense putting all the time and effort into migrating it to a new location with new features if it’s still corrupt. There is no way to over-stress the importance of good data in these situations. In order to implement a data migration enrichment strategy that drives results, it’s necessary to address these three following steps at some point in your plan.

1. Start with a Data Quality Assessment

When assessing the quality of your data, it is essential that your team has a successful method for scrutinizing data based on the following factors:

  • Accuracy
  • Completeness
  • Conformity
  • Integrity

An organization needs to have a strategy in place for managing data quality in order to ensure a successful migration, starting with an assessment of all data in the pre-migration process. According to the leading theories on data migration best practices, it’s necessary to refine your strategies for discovering and resolving data issues, and generally managing data quality into the future, before going into the migration process. This can affect the budget, timeframe and resources necessary for the data migration process, so it’s important to get this out of the way as early as possible.

2. Select a Data Enrichment Process

Once your team has weeded out the bad data, then it is necessary to select a data enrichment process that works for your specific needs. You may not need to do anything now to complete the data enrichment process, or there may be a high level of user involvement, depending on the situation. Generally, this process consists of adding external data from a variety of sources to an existing set of data in order to add value to it and increase its overall level of quality and usefulness. The process typically involves developing schema, extracting data from various sources, performing research, extracting any hard or soft copy from all relevant documents, manually sourcing data and finally checking all data for quality.

3. Consider Anticipated Outcomes

There are many benefits to having a well-thought-out data migration plan. After performing all these value-adding steps, an organization can enjoy a complete, accurate, enhanced, current and consistent set of high-quality data that boosts productivity and turnaround within the workplace. After completing a successful migration of high-quality data to an enhanced environment, it’s typical to see project completion times decrease while morale and productivity levels increase, due to the improved data accessibility, integrity, procurement and ease of use.

But how do you know when you’ve properly defined your data migration enrichment strategy? This process could be quick and painless, completed all in one day, or it could be a long and drawn-out process that could potentially go on for months or even years in some extreme cases. You’ll know you’ve created an effective data migration enrichment strategy when you’ve mapped out the sections for which data is being moved, who will participate in each aspect of each project involved in the migration enrichment process, what kind of testing you need to do and how long the transition should realistically take to come to a successful completion with all necessary data ready to use. While it won’t be a simple process, the more planning your team has done, the easier it will be to complete a successful migration.

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