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5 docs tagged with "Data Transformation Script"

Recipes that include a Data Transformation Script Component.

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Batch Data Operations with a Sub Component

This straightforward recipe demonstrates a core Conscia behaviour - interacting with an API endpoint, and executing a task per-record against the results. In this example, we will be reading and writing from an Airtable, an innovative spreadsheet-type collaboration tool. We will read from a Table and for each unserved row, perform a unit of work on that input in Conscia, then write the output to another Table.

Batch Microservice Workflows

Conscia Recipes are designed to be intentionally open-ended, providing a robust starting point for building custom workflows. However, just as Components can come togther to form more complex Flows or populate bespoke experiences, Recipes can be built using others as a foundation.

Blending Responses from Multiple Components

Many Conscia DX Engine solutions involve Orchestration Components that each invoke different Webservice APIs to gather related data. Logic to select, validate, filter, merge, and otherwise blend data can depend on data from any number of Components.

Data Caching and Merging Array-Based Data

This recipe demonstrates preparing and supplying product data for something like a highly detailed product comparison page. We are accessing data from multiple sources, and using Conscia to unify arrays of product data in real-time to deliver a richer and more performant web experience.

Merge Product and CMS data

In the following recipe, we will merge content items from the CMS with product records from a commerce engine in order to populate product pages, whether a Product Detail Page (PDP), Product Listing Page (PLP), landing page, or anywhere products are featured with extended information. This is a typical use case in a headless commerce implementation -- needing to match up additional data with product data, be it pricing or inventory or product care instructions. Frequently developers write glue code in the frontend to address this use case and end up making multiple API calls and stitching together data from the backends. An orchestration layer can configure this data unification.