A virtual data pipe is a collection of processes that gather raw data from various sources, convert it into a format that can be used by software, and store it in a place like databases. This workflow can be configured in accordance with a timetable or on demand. It can be complex and has many steps and dependencies. It should be simple to track the relationships between each step to ensure that everything is running smoothly.
After the data has been ingested, it undergoes a first cleansing and validation. The data may be transformed through processes like normalization, enrichment, aggregation, or masking. This is a crucial step, since it guarantees that only the most accurate and reliable data is utilized for analytics and application usage.
The data is then consolidated and transferred to its final storage spot and can be access for analysis. It could be a database that has a structure, such as an data warehouse, or a data lake which is less structured.
It is usually recommended to adopt hybrid architectures, where data is moved from on-premises to cloud storage. IBM Virtual Data Pipeline is an excellent option to accomplish this, since it offers an option for multi-cloud copies that allows application development and testing environments to be separated. 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/simplicity-with-virtual-data-rooms
