To perform a successful data conversion, you have to know a number of things. In this series, we have uncovered the following about our conversion:

1. Scope of the conversion
2. Infrastructure for the conversion
3. Source of the conversion
4. Target for the conversion
5. Management for the conversion
6. Testing and Quality Assurance for the conversion
7. Governance and stewardship requirements
8. Data management standards and guidelines
9. Technology for the conversion
10. Target security requirements
11. Data requirements

Now we have to consider a prototype. When examining a prototype, consider these points:

• The source to target conversion programs may be very complex, and require days (or weeks) to complete. A prototype with a sampling of data may work well as the prototype to show feasibility of the solution.
• Installation of target software or platforms may be required, consider the set up development, test and production simultaneously, to make sure all parameters are the same. This allows testing (see Number 1 above) with the SAME sampling of data on each platform. If adjustments of performance parameters are required, make the changes on Development, Test and then Production.
• We need to include the business users in this conversion! I like to include them for writing testing scenarios to validate data between the source and target for the conversion. If there is a front-end or reporting environment, consider letting the business people test that too.

My preference is to prototype a new application as soon as possible in the project. This may or may not be the best solution for your environment.