Is it better to delete a list entirely or update a list each time?

Is it better to delete a list entirely or update a list each time?

• A. Generally speaking it is better to update a list each time utilizing a unique code.
• B. It is better to delete the list entirely and recreate when changes are needed.
• C. It depends on the size of the list.
• D. It is better to preserve the old version and never update.

Answer: (A)

The idea being tested is how to manage list changes without breaking the model’s connections. The best approach is to update the list as changes happen, using a unique code for each member. The code acts as a stable identity, so you can add new members, remove old ones, or update member attributes while keeping every reference in modules, line items, and imports intact. This stability means dashboards, data mappings, and historical data continue to point to the same member even as its details evolve. Deleting the list and recreating it is risky because everything that references those members—modules, line items, imports, and even saved data—can lose their linkage. Recreating also forces re-mapping and potential data reloads, which is time-consuming and error-prone. The size of the list doesn’t change the core principle. Even with large lists, updating with a stable code is preferable to avoid breaking dependencies. Preserving an old version indefinitely leads to confusion and a drift between what the model shows and the current reality. So, updating the list each time with a unique code keeps the model accurate, consistent, and easier to maintain.

The idea being tested is how to manage list changes without breaking the model’s connections. The best approach is to update the list as changes happen, using a unique code for each member. The code acts as a stable identity, so you can add new members, remove old ones, or update member attributes while keeping every reference in modules, line items, and imports intact. This stability means dashboards, data mappings, and historical data continue to point to the same member even as its details evolve.

Deleting the list and recreating it is risky because everything that references those members—modules, line items, imports, and even saved data—can lose their linkage. Recreating also forces re-mapping and potential data reloads, which is time-consuming and error-prone.

The size of the list doesn’t change the core principle. Even with large lists, updating with a stable code is preferable to avoid breaking dependencies. Preserving an old version indefinitely leads to confusion and a drift between what the model shows and the current reality.

So, updating the list each time with a unique code keeps the model accurate, consistent, and easier to maintain.