Entities are categorized based on their functions and the type of data that they serve. The following are five categories for data entities.
- Functional or behavioral parameters.
- Required to set up a deployment or a module for a specific build or customer.
- Can include data that is specific to an industry or business. The data can also apply to a broader set of customers.
- Tables that contain only one record, where the columns are values for settings. Examples of such tables exist for Account payable (AP), General ledger (GL), client performance options, workflows, and so on.
- Simple reference data, of small quantity, which is required to operate a business process.
- Data that is specific to an industry or a business process.
- Examples include units, dimensions, and tax codes.
- Data assets of the business. Generally, these are the “nouns” of the business, which typically fall into categories such as people, places, and concepts.
- Complex reference data, of large quantity. Examples include customers, vendors, and projects.
- Worksheet data that is converted into transactions later.
- Documents that have complex structures, such a several line items for each header record. Examples include sales orders, purchase orders, open balances, and journals.
- The operational data of the business.
- The operational transaction data of the business.
- Posted transactions. These are non idempotent items such as posted invoiced and balances. Typically, these items are excluded during a full dataset copy to reduce the volume of data that is copied/migrated. Migrating completed transactions can also lead to further complexity in trying to preserve the referential integrity of related data in the new system. In general, transactions from a completed business process are not migrated in detail but in summary.
- Examples include pending invoices.