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Shared datasets and embedded datasets are two different approaches to managing and using data in various applications, particularly in the context of software development and data analytics.
Shared Dataset:
- A shared dataset is a dataset that is stored separately from the application or system that uses it.
- It is typically stored in a centralized location, such as a database, cloud storage, or a data warehouse.
- Multiple applications or services can access and use the shared dataset, making it a central source of data for various purposes.
- Changes or updates to the dataset are reflected in real-time or near-real-time across all applications that use it.
- Shared datasets are often used to ensure data consistency and reduce data redundancy.
Embedded Dataset:
- An embedded dataset is a dataset that is incorporated directly into an application or system.
- The data is stored within the application itself, typically in a structured format, such as a file, database, or configuration.
- The data is tightly coupled with the application, and it is often not designed to be used by other applications or services.
- Changes or updates to the dataset may require modifications to the application's code, and they may not be easily synchronized across multiple applications.
- Embedded datasets are often used when an application needs quick access to specific data without relying on external data sources.
Summary:
The main difference between shared datasets and embedded datasets lies in their storage and usage
Shared datasets are centralized, separate data sources accessible by multiple applications or services. They are typically maintained independently from the applications using them.
Embedded datasets are stored within the application itself and are tightly integrated with the application. They are not designed for sharing with other applications and are usually managed within the application's codebase.
The choice between shared and embedded datasets depends on the specific requirements of your application, including data sharing, consistency, and maintainability. Shared datasets are often favored for scenarios where data needs to be shared and kept consistent across multiple applications, while embedded datasets are useful when data is closely tied to a single application's functionality.
Shared datasets are centralized, separate data sources accessible by multiple applications or services. They are typically maintained independently from the applications using them.
Embedded datasets are stored within the application itself and are tightly integrated with the application. They are not designed for sharing with other applications and are usually managed within the application's codebase.
The choice between shared and embedded datasets depends on the specific requirements of your application, including data sharing, consistency, and maintainability. Shared datasets are often favored for scenarios where data needs to be shared and kept consistent across multiple applications, while embedded datasets are useful when data is closely tied to a single application's functionality.
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