What is a Virtual Data Pipeline?

A virtual data pipeline is a collection of processes which extract raw data from a variety of sources, converts it into a usable format to be used by applications, and then saves it in a destination system like a database or data lake. This workflow can be set up according to a predetermined schedule or on demand. As such, it is usually complex, with many steps and dependencies – ideally it should be easy to track each process and its relationships to ensure that all processes are functioning properly.

Once the data has been ingested it undergoes a first cleansing and validation. It can be transformed at this stage through processes like normalization enrichment, aggregation or filtering or masking. This is an essential step to ensure that only the most accurate and reliable data is used for analysis and application use.

Next, the data is collected and then moved to its final storage location where it is accessible for analysis. It could be a structured data source such as a warehouse, or a less structured data lake according to the needs of the organization.

It is generally recommended to adopt hybrid architectures, where data is transferred from on-premises to cloud storage. IBM Virtual Data Pipeline is an excellent option dataroomsystems.info/should-i-trust-a-secure-online-data-room/ to accomplish this, as it offers a multi-cloud copy solution that allows application development and testing environments to be decoupled. VDP uses snapshots and changed-block tracking to capture application-consistent copies of data and provides them for developers through a self-service interface.