Tetra Data Pipelines provide the ability to configure a set of actions to occur automatically each time new data is ingested into the Tetra Scientific Data and AI Cloud. They run automated data operations and transformations that can help you create queryable, harmonized Tetra Data, and then enrich and push that data to downstream systems.

For more information, see Tetra Data Pipelines.

What Pipelines Are Used For

You can use Tetra Data Pipelines to do any of the following:

• Harmonize data: Parse proprietary instrument output files into a vendor-neutral and scientifically relevant Intermediate Data Schema (IDS), while also storing the data in SQL tables.
• Transform data: Add calculated fields to standard data fields.
• Contextualize files: Add attributes to files to improve how retrievable they are by search. For example, you can use Tetra Data Pipelines to programmatically add information about samples, experiment names, and laboratories.
• Enrich files: Get information from other files within the Tetra Scientific Data and AI Cloud to augment new data.
• Convert file formats: Convert IDS JSON files to other formats, such as ADF or CSV.
• Push data to third-party applications: Send data to an electronic lab notebook (ELN), laboratory information management system (LIMS), analytics application, or an AI/ML platform.

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NOTE

To extend the capabilities of Tetra Data Pipelines and the TDP, you can also create your own custom self-service Tetra Data pipelines (SSPs).