A virtual data pipeline is a set of procedures that take raw data from a variety of sources, transforms it read new article at dataroomsystems.info into an actionable format to be used by applications and then saves it in a destination system such as a database or data lake. This workflow is able to be set according to a set schedule or as needed. It is often complicated, with many steps and dependencies. It should be simple to track the relationships between each process to make sure that everything is running smoothly.
Once the data has been consumed, some initial cleansing and validation occurs. It may be transformed by using processes such as normalization, enrichment aggregation filtering or masking. This is a crucial step since it ensures only the most precise and reliable data will be utilized for analytics.
The data is then consolidated and transferred to its final storage spot and can be accessible for analysis. This 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 usually recommended to implement hybrid architectures in which data is transferred from on-premises to cloud storage. To achieve this, IBM Virtual Data Pipeline (VDP) is an excellent choice because it is an efficient multi-cloud copy control solution that allows for applications development and test environments to be separate from 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.