As data flows among applications and processes, it takes to be compiled from a number of sources, transported across systems and consolidated in one place for digesting. The process of gathering, transporting and processing the results is called a virtual data pipeline. It generally starts with ingesting data by a origin (for example, database updates). Then it moves to its destination, which may be a data warehouse just for reporting and analytics or perhaps an advanced data lake intended for predictive stats or equipment learning. At the same time, it goes thru a series of improve and processing methods, which can include aggregation, filtering, splitting, merging, deduplication and data replication.
A typical pipe will also have metadata associated with the data, that is used to track where it came from and how it was processed. This can be used for auditing, protection and conformity purposes. Finally, the pipe may be delivering data as a service to other users, which is often known as the “data as a service” model.
IBM’s family of check data managing solutions includes Virtual Data Pipeline, which supplies application-centric, SLA-driven motorisation to accelerate application creation and assessment by decoupling the management dataroomsystems.info/ of test copy data coming from storage, network and web server infrastructure. It will do this simply by creating online copies of production info to use meant for development and tests, while reducing you a chance to provision and refresh those data clones, which can be about 30TB in dimensions. The solution as well provides a self-service interface designed for provisioning and reclaiming digital data.