A virtual data pipe is a collection of processes that extract raw data from different sources, transform it into an appropriate format to be used by applications, and then store it in a place like a database. The workflow can be programmed to run according to a timetable or on demand. It is usually complex and has many steps and dependencies. It should be simple to monitor the connections between each step to ensure that it is working correctly.
After the data is consumed, some initial cleaning and visit their website https://dataroomsystems.info/data-rooms-for-better-practice/ validating is performed. It could also be transformed through processes such as normalization and enrichment aggregation filtering as well as masking. This can be an important step to ensure that only the most reliable and accurate data is used for analytics and application use.
Then, the data gets consolidated and moved to its final storage space where it can be easily accessed for analysis. It could be a database with some structure, such as the data warehouse, or a data lake that is not as structured.
To accelerate deployment and enhance business intelligence, it’s often recommended to implement an hybrid architecture in which data is transferred between on-premises and cloud storage. To achieve this, IBM Virtual Data Pipeline (VDP) is a great choice because it is an efficient multi-cloud copy control solution that enables the development and testing environments of applications 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.