Data.Quality.Assessment.2016.jpgHaving usable data is critical, and is indeed the rationale behind any data migration. Not only should data retain the same level of quality by the end of a successful migration, but ideally content should be greatly enriched by the end of the process.

The goal should be to ensure regulatory compliance and provide easily accessible information, intuitive search processes, enriched data sets and an effective information architecture with 100 percent of the enterprise’s data intact.

There are a number of different ways to approach data enrichment and migration.

These include doing nothing, keeping enrichment in place, migrating content as-is or as-is with future data enrichment plans or implementing minimal, intelligent or complete data enrichment. Of course, a complete data enrichment plan is ideal, which may include any number of customized strategies to refine and enhance raw data and data sets.

The first step, however, is conducting a thorough Data Quality Assessment to ensure that all data is unscathed and fully functioning before, during and after the migration. This also ensures that the enterprise content management system is performing to specifications.

What is a Data Quality Assessment?

Data.Quality.Assessment.Checklist.jpgA Data Quality Assessment on the enterprise’s source system identifies areas of risk or issues with the migration. More specifically, that means areas that will not affect the ability to migrate but could affect the usability of the system, or areas that need to be addressed because they directly impact the system’s ability to migrate.

A Data Quality Assessment Report should be produced addressing the areas of accuracy, completeness, conformity and integrity. Key information to gather during Data Quality Assessment reporting includes:

  • Percentage of acceptable risks and issue data.
  • Summary of key findings.
  • Summary of opportunities to enrich data.
  • Identification of specific issues.
  • Recommended approach to address those issues.
  • Summary of the overall assessment.

A Data Quality Assessment on the source system should identify areas of risk and potential issues with the migration, including areas that will not affect the ability to migrate but could affect the usability of the system, and issues that directly impact the ability to migrate and the value of your data.

For each area, the assessment should report on a number of key pieces of information. These include summaries of key findings, opportunities to enrich data and an overall assessment. The assessment should also address any specific issues that have been identified and recommend an approach to address those issues. Relevant statistics should also be included, such as the percentage of acceptable risk and issue
data to be reported.

With this vital information, it is then possible to identify opportunities to enrich the information architecture, taxonomy and access to information - ensuring migration timeline and cost is realized with the utmost care given to data requirements and technicalrequirements, including system information.

5 Keys to a Successful ECM Migration