A virtual data pipe is a collection of processes that extract raw data from different sources, convert it into an appropriate format to be utilized by programs, and save it to a destination like databases. This workflow is able to be set according to a schedule or dataroomsystems.info/should-i-trust-a-secure-online-data-room/ on demand. This is often complex, with lots of steps and dependencies – ideally it should be able to track each step and its interrelations to ensure that all operations are functioning properly.
Once the data has been ingested it is subjected to a preliminary cleaning and validation, and can be transformed by processes such as normalization, enrichment, aggregation or masking. This is an important step because it guarantees only the most accurate and reliable data can be used for analysis.
Next, the data is consolidated and moved to the final storage location where it is easily accessible for analysis. This could be a structured one such as a warehouse or a less structured data lake, according to the needs of the company.
To accelerate deployment and enhance business intelligence, it’s often beneficial to utilize an hybrid architecture in which data is transferred between cloud storage and on-premises. For this to be done efficiently, IBM Virtual Data Pipeline (VDP) is a good choice because it is an efficient multi-cloud copy management solution that allows the development and testing environments of applications to be decoupled 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.
