What is a Virtual Data Pipeline?

A virtual data pipeline is a collection of processes that collect raw data from different sources, converts it into a usable format to be used by applications, and then saves it in a destination system such as a database or data lake. This workflow can be set up in accordance with a timetable or on demand. It is often complex with a lot of steps and dependencies. It should be easy to keep track of the relationships between each process to make sure that everything is running smoothly.

Once the data has been ingested it goes through a process of initial cleansing and validation. It could be transformed through processes like normalization enrichment, aggregation, or masking. This is a crucial process because it ensures that only the most precise and reliable data can be used in analytics.

The data is then consolidated and moved to its final storage location where it can be easily accessed for analysis. It could be a database that has some structure, such as a data warehouse, or a data lake which is not as structured.

It is often desirable to implement hybrid architectures in which data is transferred from storage on premises to cloud. IBM Virtual Data Pipeline is an excellent option to accomplish this, since it offers an option for multi-cloud copies that allows application development and testing environments to be separated. VDP uses snapshots and changed-block tracking to capture application-consistent copies of data and provides them for developers through a self-service interface.

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