Use data entities for data management and integration
Table of Content:
Data entities provide conceptual abstraction and encapsulation (de-normalized view) of underlying table schema that represent data concepts and functionalities.
After data entities are created, you should be able to reuse them for Excel add-ins, import and export, or integration scenarios. A data entity is an abstraction from the physical implementation of database tables.
This image presents data entity integration scenarios.
For example, in normalized tables, a lot of the data for each customer might be stored in a customer table, and then the rest might be spread across a small set of related tables. In this case, the data entity for the customer concept appears as one de-normalized view, in which each row contains all the data from the customer table and its related tables.
A data entity encapsulates a business concept into a format that makes development and integration easier. The abstracted nature of a data entity can simplify application development and customization. Later, the abstraction also insulates application code from the inevitable churn of the physical tables between versions.
A data entity has the following capabilities:
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It provides a single stack to capture business logic, enable scenarios such as import and export, integration, and support additional logics by a developer adding code.
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It becomes the primary mechanism for exporting and importing data packages for Application Lifecycle Management (ALM) and demo data scenarios.
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It can be exposed as OData services, and then used in tabular-style synchronous integration scenarios and Microsoft Office integrations.