A virtual data pipe is a collection of processes that extract raw data from various sources, convert it into an format that can be utilized by applications, and save it to a destination like the database. This workflow can be configured to run according to a timetable or on demand. It is usually complex, with many steps and dependencies. It should be easy to monitor the connections between each process to ensure that it’s working properly.
Once the data has been taken in, a preliminary cleaning and validating takes place. It can also be transformed using processes such as normalization or enrichment aggregation filters, or masking. This is an essential step, since it guarantees that only the most accurate and reliable 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 to analyze. It could be a data warehouse with an organized structure, like the data warehouse, or a data lake which is not as structured.
To accelerate deployment and increase business intelligence, it’s usually preferable to employ a hybrid structure where data is transferred between cloud and on-premises storage. To achieve this, IBM Virtual Data Pipeline (VDP) is a great choice as it provides an efficient multi-cloud copy control solution that enables applications development and test environments to be decoupled 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.
https://dataroomsystems.info/how-can-virtual-data-rooms-help-during-an-ipo
Lascia un commento