What is a Virtual Data Pipeline?

A virtual data pipeline is a set of processes that collects raw data from source systems and transforms it into an actionable format to be used by applications. Pipelines can be used for a variety of reasons, including reporting, analytics and machine learning. They can be programmed to run data on a timetable or on demand. They are also able to be used for real-time processing.

Data pipelines can be complex with a variety of steps and dependencies. For instance, the data generated by one application could be fed into several other pipelines, and then feed into different applications. It is crucial to monitor the processes and their interactions to ensure that the pipeline is operating correctly.

There are three primary uses of data pipelines: accelerating development, enhancing business intelligence and mitigating risk. In each of these cases it is the intention to take a large amount of data and then transform it into a form that can be utilized.

A typical data pipeline would comprise many transformations such as reduction, filtering and aggregation. Each transformation stage may require a different database. Once all transformations have been completed the data is then pushed into the destination database.

To reduce the time it takes to capture and transport data Virtualization technology is commonly employed. This allows the use of snapshots and changed-block tracking to capture application-consistent copies of data in a much faster way than traditional methods.

With IBM Cloud Pak for Data powered virtual data pipeline by Actifio you can quickly deploy a virtual data pipeline that will enable DevOps and speed up cloud data analytics as well as AI/ML initiatives. IBM’s patented virtual data pipeline solution is an integrated copy management system for multiple cloud platforms that allows test and development environments to be decoupled from production environments. IT administrators can swiftly enable development and testing by provisioning encrypted copies of databases on-premises using the self-service GUI.