What is a Virtual Data Pipeline?

A virtual data pipe is a collection of processes that take raw data from various sources, convert it into the format that can be used by applications, and then store it in a place like the database. This workflow can be configured to run according to the timetable or at any point. It is usually complex with a lot of steps and dependencies. It should be easy to monitor the connections between the various processes to ensure that it’s running as planned.

After the data has been ingested it undergoes some initial cleaning and validation, and can be transformed through processes like normalization enrichment, aggregation or filtering or masking. This is a crucial step as it ensures only the most accurate and reliable data can be used for analytics.

The data is then consolidated before being moved to the final storage location in order to be accessed for analysis. It could virtual data pipeline be a database with an organized structure, like a data warehouse or a data lake that is less structured.

To accelerate deployment and increase business intelligence, it’s often preferable to employ an hybrid architecture in which data is moved between on-premises and cloud storage. To achieve this, IBM Virtual Data Pipeline (VDP) is an excellent choice since it offers an efficient multi-cloud copy management solution that allows the development and testing environments of applications to be separate from the production infrastructure. 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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