A virtual data pipe is a set processes that transform raw data from source systems into a format that can then be accessed by software. Pipelines can be used for a variety of reasons, including reporting, analytics, and machine learning. Pipelines can be set to process data dataroomsystems.info/ on a predefined schedule or on demand, and may also be used for real time processing.
Data pipelines are often complex with many steps and dependencies. For instance the data generated by a particular application may be fed into several other pipelines, which feed into different applications. It is crucial to be able to track the processes and their interactions to ensure that the pipeline operates properly.
Data pipelines can be used in three main ways: to accelerate development, improve business intelligence, and decrease risk. In each of these cases it is the intention to take a large amount of data and turn it into a form that can be used.
A typical data pipeline contains a series transformations such as filtering and aggregation. Each stage of transformation might require a different database. Once all transformations have been completed, the data is pushed into the destination database.
To reduce the time it takes to collect and transfer data Virtualization technology is often used. This allows the use of snapshots and changed-block tracking to capture application-consistent copies of data in a much faster way than traditional methods.
With IBM Cloud Pak for Data powered by Actifio you can deploy an automated data pipeline to help DevOps operations and accelerate cloud data analytics and AI/ML projects. The patented virtual pipe solution by IBM offers a reliable multi-cloud copy management platform that separates development and test infrastructure from production environments. IT administrators can set up masked copies of on-premises databases through a self-service interface in order to facilitate development and testing.
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